Category: Demo Day

A Community in Action: The Questions That Sparked Deeper Insight at Demo Day 12

Posted on by Jim Smith

Last week, at our 12th Demo Day, we saw six fintech founders succinctly showcase their solutions to the most pressing challenges in financial services. Their companies built these solutions during their recent participation in our Data Access Residency with the support of several of our Data Partners.

The presentations were fast paced, and some of you may have missed the interactions between founders and members of the audience. So, here are a few of the questions audience members asked after seeing what these teams have built, and the answers these founders provided.

Demo Day 12 logo

Agxes

Victoria Tostado Bringas is Co-founder and CEO of Cambridge-based Agxes. Agxes is bringing artificial intelligence to agricultural lending, using it to help bridge the gap between bankers and farmers by tackling the inefficiencies and system challenges in agricultural lending today. While taking part in the Data Access Residency, they worked with Equifax, using their Sandbox to explore their credit data and integrating credit reports into the lending workflow, evaluating behavior for ag loan repayment models.

Q.   Victoria, what should we know about the Farmer Wallet?

A.   The Farmer Wallet turns lending into continuous financial intelligence. It gives lenders real-time visibility into how funds are used, helping monitor risk, detect red flags, and design better financial products. For farmers, it provides live visibility into cash flow and expenses while automatically organizing records for accounting and future credit access. It increases transparency, efficiency, and value for both sides.

Q.   Are non-banking financial institutions also important agricultural lenders?

A.   Yes! Actually, it is a considerable segment that we serve, too.

CleverChain

Daniele Azzaro, Co-founder and CEO of London-based fintech CleverChain. CleverChain is a next-generation regtech platform that transforms compliance with AI-driven, real-time, global due diligence and automated risk intelligence. It empowers financial institutions to onboard faster, stay fully compliant, and eliminate manual work with unparalleled speed, accuracy, and scale.

CleverChain was able to accelerate product development by working with high-quality datasets from Equifax while participating in the Data Access Residency. This allowed them to test, validate, and refine their AI models across global corporate, ownership, and risk data.

VERA is an AI-powered Due Diligence Specialist designed by CleverChain to transform how compliance teams operate –– delivering end-to-end compliance reviews in minutes.

Q.   Daniele, is VERA running in the cloud, on premises, or do you give clients a choice?

A.   Our default solution is in the cloud, but it can be integrated to any internal systems via API.  For any questions or to try it feel free to reach out at daniele.azzaro@cleverchain.ai!

Q.   When VERA automatically discards a match as irrelevant, does the audit trail capture the reasoning for the discard, or just the outcome?

A.   Yes, and it’s able to do this with greater context and confidence than historical legacy systems as it doesn’t rely anymore on the limited fields that can be contained in a database.  We have successfully tested this approach with regulators and very large global banks who have compared results against all the main tools in the market.

Q.   Are you talking to prospects in North America as well as in Europe?

A.   We are on-boarding our first customer in the US.  Europe is our main market but we have some customers in Asia. We are currently looking for partners to scale the US market.

DigsFact

Nishant Tomar is Chairman and CEO of Chicago-based regtech startup DigsFact. DigsFact’s Agentic AI-based fraud engine uses human-like reasoning at machine speed to prevent financial crime like fraud and money laundering in any transaction, in less than 1 millisecond. Transactions can be traditional, like check, ACH, wire and cards (credit, debit) or modern like RTP, A2A, Wallet to Wallet, etc. They can be domestic or cross-border or use digital currencies. DigsFact also worked with Equifax while taking part in the Data Access Residency.

Their proprietary product —  the PreCogs —  was created to augment existing fraud and money laundering solutions to reduce financial crime and lower the cost of manual reviews.

Q.   Nishant — How long does it take your average client to implement your solution?

A.   The short answer is it depends on the use case — if the implementation is for ACH, wire, instant payments / RTPs, etc., the fastest implementation we have done was in one month but that required commitment from our customer as well. I am happy to connect and learn more to give a more specific answer for your use case. Please feel free to email me at nishant@digsfact.com.

Q.   Have you started any work on voice analysis and voice agent fraud prevention?

A.   In 2026, we started working with one financial institution on detecting fraud in back-office channels such as calls, forms, etc. The fraudsters are getting extremely good at cloning voice and that’s where our approach to detecting intent drift, behavior anomalies, etc., can be effective to catch even the best voice cloning fraudster even after the voice matches.

I am happy to share more about what we are doing there.

Q.   Are the PreCogs able to identify and prevent synthetic identity fraud?

A.   Yes. Using a variety of techniques like behavior inconsistency, intent drift, network and relationship intelligence, GAN-based learning, etc., we can detect synthetic identity fraud. Happy to discuss this in more detail.

Gemsen

Charlie Ko is Co-founder and CEO of Boston-based fintech Gemsen. Gemsen allows organizations to harness the power of machine learning without exposing sensitive data, ensuring complete compliance with data protection regulations. Whether applied within workflows such as insurtech, regtech, fraud detection, credit analytics, compliance, or investment research, Gemsen enables secure collaboration throughout the entire process.

Massive, one of our Data Partners, provided Gemsen with an extremely rich data set of market flow information spanning many years. Since data is the fuel that powers AI/ML, their clean and reliable data made testing easier for Gemsen. Billions of rows of data flowing at millisecond speed helped Gemsen prove their reliability and improve their capabilities.

Q.   Charlie, what types of firms would you like to be able to test with?

A.   We have ongoing tests with a variety of financial service firms. We’re always looking to add any firms that are trying to wrap their head around massive data volume and pattern detection.

Q.   Is Gemsen hiring?

A.   We are always opportunistic and looking for folks that are interested in advancing the technology and applications of machine learning.

Menos AI

Junchen (William) Wu is Co-Founder & CEO of California-based Menos AI. Menos AI is designed to generate, evaluate, and validate alpha ideas for institutional investors. The system transforms unstructured market content into structured trade ideas, identifies the most credible signals, and supports end-to-end testing across different market conditions. Through the Data Access Residency, Menos AI was able to work with leading data providers including FactSet and S&P Global.

Q.   William, are there any asset classes Menos AI doesn’t cover?

A.   We are a true multi-asset AI-powered research and portfolio management system. Today we focus on fixed-income and global macro (i.e. FX, commodity, rates, etc.).

Q.   What size (AUM) asset managers are you targeting?

A.   We work with a wide range of institutional investors managing from $1 billion to $1+ trillion in AUM.

Q.   Do you integrate or plan to integrate other data sources aside from internal and broker research?  (i.e. transcripts, filings, structured data, etc.)

A.   Yes! We have already integrated filings, transcripts and structured market data. We welcome more data partners to reach out to partner with us and bring the value of data to the buyside.

sumtyme.ai

London-based sumtyme.ai, an AI research lab, has built a universal framework for navigating complex systems, from the volatility of global financial markets to the unpredictability of atmospheric patterns. Ade Jinadu, is a Co-Founder.

The lab has pioneered a form of autonomous intelligence focused on causality rather than statistical pattern recognition. Their technology solves the inherent lag of statistical AI, offering a universal understanding of change in the world’s most critical systems. High-quality time-series data from Massive was instrumental in their recent case studies and POCs, and allowed sumtyme.ai to prove the strength of their framework in live market environments.

Q.   Ade, what does it mean to say that sumtyme is an AI research lab?

A.   That we are focused on making new algorithmic and architectural breakthroughs to better understand complex systems like the financial markets breaking away from the current focus on neural networks & deep learning.

Q.   Are there any bank use cases?

A.   Yes! For banks, our initial use case is proactive risk management for your instrument/portfolio level risk.

Q.   Ade, what is the business model at sumtyme.ai?

A.   Our business model is to license our underlying technology via an API as a SAAS or provide the risk insights through a GUI dashboard.

* * * * *

If you’d like to talk to any of these entrepreneurs about what they are building, please reach out to us here. If you weren’t able to attend, we will post a recording of the six startup presentations, as well as insights from thought leaders representing the EY, Morningstar, and Goodwin, to our YouTube channel shortly.

 

Meet Menos AI — A Demo Day 12 Presenting Startup

Posted on by Jim Smith

This year, Fintech Sandbox Demo Day will take place on Tuesday, April 28. The presentations will be virtual and the event, as always, is free. Demo Days are exciting because we get to showcase startups that are on the very cutting edge of innovation and you get to see what they’re up to before they’re discovered.

Over the last few weeks, we’ve been highlighting this year’s presenting entrepreneurs. Today, we’re talking to Junchen (William) Wu, Co-Founder & CEO of California-based Menos AI.

Menos AI is building a central intelligence system for asset management, combining the capabilities of a financial information terminal with the judgment of a senior analyst. It is designed to generate, evaluate, and validate alpha ideas for institutional investors. The system transforms unstructured market content into structured trade ideas, identifies the most credible signals, and supports end-to-end testing across different market conditions.

Junchen (William) Wu, Co-Founder & CEO of California-based Menos AI.
Junchen (William) Wu

William, tell us a bit about Menos AI. What problems are you solving? What makes your approach different?

Menos AI is building the AI-native central intelligence system for asset management.

Today, a portfolio manager typically has six screens in front of them — Bloomberg, OMS, portfolio systems, risk tools, research feeds. All showing different pieces of information, but not connected. Even with AI tools, they still have to jump between systems and stitch things together themselves.

We solve this by bringing everything into one AI-native layer. Our system connects across all these tools, understands the full context, and gives you a clear, unified view.

What makes us different is simple: we’re not another screen. We replace the need for all those screens by turning fragmented data into one source of intelligence.

What is your company’s origin story?

The idea for Menos AI was derived from my experience as Head of Quant at Northern Trust’s Front Office Solutions. My role was to help hedge funds and large asset managers manage their data, including investment book of records, risk, accounting, portfolio analytics, and compliance, etc. What I saw consistently was fragmentation everywhere: different systems, siloed data, and no unified view.

We started addressing this by building what we called a “Total Portfolio View”, bringing everything into one place so investment teams could finally see the full picture.

Menos AI is the next step of that idea with the power of AI. Instead of just aggregating data, we’re turning it into intelligence by using AI to not only unify information, but also understand it and help drive better decisions.

Who is your target market?

Our target market is institutional investors: hedge funds, asset managers, pension funds, and family offices. These are highly regulated organizations dealing with large amounts of data, complex workflows, and high-stakes decisions. They don’t just need AI tools. They need a system that is secure, compliant, and can bring everything together to help them make better investment decisions.

What do you mean when you say the distinction between AI-enabled and AI-native is existential for asset managers?

AI-enabled means you’re adding AI on top of existing workflows, like summarizing reports or helping with notes. It makes things a bit faster, but the core process doesn’t change. AI-native means the workflow itself is built around AI. The system continuously reads information, connects it to the portfolio, and generates insights in real time. The difference is scale and speed.

* If you stay AI-enabled, you get incremental improvement.
* If you become AI-native, you operate in a completely different way.

In asset management, where information and timing drive returns, that gap becomes existential.

Which Fintech Sandbox Data Partners have you worked with?

Through Fintech Sandbox, we’ve worked with leading data providers like FactSet and S&P Global.

What were you able to demonstrate based on access to this data?

We were able to demonstrate that structured and reliable data is the foundation for truthful AI. With access to high-quality data from providers like FactSet and S&P Global, we showed that our platform can ingest this data, connect it with portfolio context, and turn it into actionable insights. More importantly, we can use AI to generate results that are explainable, traceable, and deterministic, which is critical for institutional use. In simple terms, this brings AI from a black box into something investment teams can actually trust and use in real decisions.

What milestones has Menos AI achieved so far?

We’ve achieved strong early milestones across product, market validation, and client adoption. First, we successfully launched our product, and it was shortlisted by Hedgeweek as “New Product of the Year,” which is strong recognition from the industry.

Second, we’ve been recommended as a top institutional-grade AI solution for asset management by major prime brokerage consulting teams, who are introducing us to their hedge fund clients.

Third, on the client side, we’re already working with multiple leading global asset managers, supporting teams that manage trillions of dollars.

Can you describe what it’s been like to be part of the Fintech Sandbox community?

Being part of the Fintech Sandbox community has been incredibly valuable for us, especially at this stage of building Menos AI.

What stands out most is access — not just to high-quality institutional datasets like FactSet and S&P Global, but to a broader ecosystem of partners who understand how financial infrastructure actually works. In our space, structured and reliable data is the foundation for building truthful, institutional-grade AI. Fintech Sandbox gave us the ability to prototype and demonstrate that our system can generate explainable, traceable, and deterministic outputs on top of that data.

Beyond the data, the community itself is very high signal. You’re surrounded by founders and teams who are tackling real problems in financial services, not just building surface-level applications. That creates a very different kind of conversation, more focused on scalability, compliance, and real-world deployment.

It’s also been a great platform for visibility. Being part of the Sandbox has helped us engage with major institutions and validate that what we’re building is not just interesting, but actually needed.

What’s next for Menos AI?

First, scaling adoption — expanding from early clients and design partners to broader enterprise deployments.

Second, deepening the product — continuing to build out the platform into a true central intelligence layer, with more advanced, explainable AI workflows that investment teams can rely on.

Third, defining the category — helping the industry move from fragmented tools to AI-native infrastructure.

Our long-term goal is simple: every investment organization will have its own AI-powered central intelligence and we want to be the platform that makes that possible.

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To hear more about Menos AI and five additional exciting fintech startups, be sure to register for Fintech Sandbox Demo Day 12!

Meet DigsFact — A Demo Day 12 Presenting Startup

Posted on by Jim Smith

This year, Fintech Sandbox Demo Day will take place on Tuesday, April 28. The presentations will be virtual and the event, as always, is free. Demo Days are exciting because we get to showcase startups that are on the very cutting edge of innovation and you get to see what they’re up to before they’re discovered.

Over the next few weeks, we’ll highlight this year’s presenting entrepreneurs. Today, we’re talking to Nishant Tomar, Chairman and CEO of Chicago-based regtech startup DigsFact.

There has been a significant rise in AI driven fraud attempts that mimic customer identity and bypass rule-based fraud engines. DigsFact’s Agentic AI based fraud engine uses human-like reasoning at machine speed to prevent financial crime like fraud and money laundering in any transaction, in less than 1 millisecond. Transactions can be traditional, like check, ACH, wire and cards (credit, debit) or modern like RTP, A2A, Wallet to Wallet, etc. They can be domestic or cross-border or use digital currencies.

Nishant Tomar, Chairman & CEO of DigsFact.

Nishant, tell us a bit about DigsFact. What problems are you solving? What makes your approach different?

DigsFact is a team of people who convert their dreams and aspirations into reality and tangible achievements with the power of Artificial Intelligence. Our proprietary product – The PreCogs (https://theprecogs.ai/) – was created to augment existing fraud and money laundering solutions to reduce financial crime and lower the cost of manual reviews.

While all existing financial crime (fraud and money laundering) solutions are focused on identity validation and authentication, we complement them by detecting financial crime based on behavioral anomalies and a dynamic rule engine that is evolving on its own. For example, every fraud attempt introduces brand new rules in our fraud engine, so that the fraudster is constantly chasing a moving target. We also predict new crime patterns before they emerge, keeping us one step ahead of the fraudsters.

What is your company’s origin story?

I have spent most of my career in financial services, so I was aware of fraud being a pain point, but I never knew the extent of the problem. When I met one of the executives of Swift at one of the conferences abroad, he shared how the problem of financial crime – fraud and money laundering – is growing worldwide despite all the existing solutions.

Coincidentally, when I returned home from that trip, my wife and I witnessed my brother-in-law lose a big chunk of money within a matter of minutes, while he was with us. I saw him getting a series of SMS alerts from his credit card as well as the bank that issued his debit card. By the time he called each of them, his bank account balance was almost nothing and his credit card was already maxed out. Without getting into the details of how this fraud occurred, this whole thing happened while he was trying to book a rental car – or at least that’s what my brother-in-law thought he was doing. I was there so I saw most of it LIVE, although I wasn’t paying much attention to what he was doing until he told me he is getting SMS alerts about the repeated money withdrawals.

Could this have been avoided? I am sure with the benefit of hindsight, we can think of ways to avoid it. However, I noticed how the fraudsters were using more sophisticated techniques and how creative they were in fooling someone. I also remembered the conversation I had with the Swift executive, at the conference I just came back from, about fraud being a global phenomenon. I realized that if nothing is done, it’s only a matter of time before these fraudsters play a trick on me or my kids at some point in the future.

We gather you’re a fan of the film Minority Report.

Yes 🙂 Love the movie. Loved the concept of preventing crime by detecting it before it happened. That’s why we named our product – The PreCogs – with 2 main differences:

  1. The movie had three precogs and we have two – one for fraud and the other for money laundering
  2. The movie was focused on preventing crime like murders while we are focused on preventing financial crime like fraud and money laundering.

Who is your target market?

We have operations in the US and India but our customers have operations worldwide.

  • For customers – we are focused on financial institutions like banks, credit unions, and insurance companies.
  • For partnerships – we are focused on partnering with existing fraud solutions that focus on ID validations and authentications where our Agentic AI approach compliment their solution to reduce false positives and missed detections.

Does your product augment or replace existing payment fraud solutions?

It augments existing payment fraud solutions.

Which Fintech Sandbox Data Partners have you worked with?

Equifax.

What milestones has DigsFact achieved so far?

  • Crossed 25 millions transactions per day.
  • Saved $2.8 million in median losses annually per customer.
  • Reduced cost of manual reviews for our customers by 70%.

Can you describe what it’s been like to be part of the Fintech Sandbox community?

Fintech Sandbox offers a very unique value proposition for the startups – specially to fintechs. Any fintech founder can tell you that it is very helpful to have easy access to data partners, but even more importantly, there are opportunities to even partner together with those data partners, if the synergies exist. We have come a long way in the past 12 months, since joining the Fintech Sandbox community and we continue to look forward to collaborating further within the community.

What’s next for DigsFact?

We have enjoyed exceptional growth in the last two years and signed two major strategic partnership deals in the past six months. We continue to stay focused on surpassing our own growth record this year (2026) through continued strategic partnerships, where it makes sense. If you are interested in learning more, you can check out our website at https://theprecogs.ai/ or contact me at nishant@digsfact.com

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To hear more about DigsFact and six additional exciting fintech startups, be sure to register for Fintech Sandbox Demo Day 12!

Meet sumtyme.ai — A Demo Day 12 Presenting Startup

Posted on by Jim Smith

This year, Fintech Sandbox Demo Day will take place on Tuesday, April 28. The presentations will be virtual and the event, as always, is free. Demo Days are exciting because we get to showcase startups that are on the very cutting edge of innovation and you get to see what they’re up to before they’re discovered.

Over the next few weeks, we’ll continue highlight this year’s presenting entrepreneurs. Today, we’re talking to Ade Jinadu, Co-Founder of London-based sumtyme.ai. Operating as an AI research lab, sumtyme.ai has built a universal framework for navigating complex systems, from the volatility of global financial markets to the unpredictability of atmospheric patterns.

The lab has pioneered a form of autonomous intelligence focused on causality rather than statistical pattern recognition. Their technology solves the inherent lag of statistical AI, offering a universal understanding of change in the world’s most critical systems.

Ade Jinadu, Junchen Co-Founder of UK-based sumtyme.ai.

Ade, tell us a bit about sumtyme.ai. What problems are you solving? What makes your approach different?

The current AI paradigm suffers from a built-in statistical lag, as it must wait for patterns to become significant before it can identify change. In high-stakes environments like finance, this delay is often costly because by the time a shift is statistically recognised, the opportunity has passed or the crisis has already occurred.

We are solving this by building a machine that treats the entire world as a network of interconnected data streams. Starting with the global financial system, our proprietary architecture observes every pulse in real-time, using a mathematical understanding of causality to autonomously track change from the moment it begins. This continuous learning framework eliminates the reliance on training data, re-training or context graphs.

What is your company’s origin story?

We built sumtyme.ai out of a shared team frustration: the attempt to predict change using traditional neural networks. We spent eight years engineering a framework that eliminates the industry’s greatest bottlenecks: massive training datasets, large-scale compute and the constant need for retraining.

What do you mean when you say you’ve developed the first intelligence layer for the global financial system?

We have built the first true intelligence layer by leveraging Causal AI that understands the underlying mechanics of how change forms and evolves, rather than the pattern-based guesswork of Predictive AI.

An intelligence layer for global markets should never require asset-specific training or a “retraining break”. We are the first lab to demonstrate technology capable of autonomously identifying systemic change at the point of inception, operating in real-time across any publicly traded asset and independent of historical context.

Who is sumtyme.ai’s target market?

We are shifting the financial industry from reactive panic to proactive management across three key pillars:

  • Central Banks: Autonomous monetary policy monitoring.
  • Commercial Banks: Real-time systemic health tracking.
  • Hedge Funds: Information advantages that capture alpha before risk is priced in.

Which Fintech Sandbox Data Partners have you worked with?

We are incredibly grateful to Massive for working with us and providing timely feedback to all our questions. Their high-quality time series data was instrumental in our recent case studies and POCs, allowing us to prove the strength of our framework in live market environments.

What were you able to demonstrate based on access to this data?

Access to this data allowed us to validate our framework against two of the most volatile events of the last 20 years: the 2008 Financial Crisis and the 2020 COVID-19 crash. By identifying and tracking causal shifts in time-series data before the market panic, we demonstrated the ability to mitigate drawdowns by 99%.

We did not try and analyse external factors to predict the virus or the subprime collapse. Instead, we demonstrated how our framework identifies systemic breakdowns by analysing the underlying time-series of each asset with zero reliance on external context, manual labelling, or historical training sets.

What milestones has sumtyme.ai achieved so far?

Our technology is now fully in production. We have achieved six months of testing with zero downtime and 94% directional accuracy. With pilots currently underway, we have moved into our next phase: forming a consortium to organise a private Effective Challenge with several G-SIBs.

Can you describe what it’s been like to be part of the Fintech Sandbox community?

Our experience with the Fintech Sandbox community has been great. From the core team to partners like Massive and other startups, the community has provided a real-time testing ground for our causal framework. The access to institutional feedback and high-quality data provides a level of value that far exceeds what is advertised.

What’s next for sumtyme.ai?

Having validated our framework in live markets and against the market’s most volatile periods, our focus is now on scaling our solution across global markets. We are moving beyond the reactive models to a world where risk is managed at the point of inception. By providing insights that are fully explainable, auditable and traceable, we are removing market uncertainty and replacing it with mathematical transparency.

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To hear more about sumtyme.ai and five additional exciting fintech startups, be sure to register for Fintech Sandbox Demo Day 12!

Meet Agxes — A Demo Day 12 Presenting Startup

Posted on by Jim Smith

This year, Fintech Sandbox Demo Day will take place on Tuesday, April 28. The presentations will be virtual and the event, as always, is free. Demo Days are exciting because we get to showcase startups that are on the very cutting edge of innovation and you get to see what they’re up to before they’re discovered.

Over the next few weeks, we’ll highlight this year’s presenting entrepreneurs. Today, we’re talking to Victoria Tostado Bringas, Co-founder and CEO of Cambridge-based fintech Agxes. Agxes is bringing artificial intelligence to agricultural lending, using it to help bridge the gap between bankers and farmers.

Victoria Tostado Brigas, Co-founder and CEO of Cambridge-based fintech Agxes.

Victoria, tell us a bit about Agxes. What problems are you solving?

At Agxes, we are tackling the inefficiencies and system challenges in agricultural lending. Today, the process for farmers can take anywhere between 30-90 days. For farmers, we solve for a:

  • Very long lending process
  • Compliance hurdles
  • Little standardization

For lenders, we offer:

  • Operations optimization
  • New sources of income

What is your company’s origin story?

I have been a farmer for 7 years and have firsthand experience of the ag lending process and the difficulty of translating operational data to financials. Also, I have been and independent consultant for a development bank. Having the opportunity to work from both perspectives, I knew I wanted to solve this global problem.

I met Oscar Guardado, our CTO, at MIT. He is a national physics olympiad absolut gold medalist working in ag-tech, so the timing was right.

What is different about agronomic data?

  • Domain expertise is required to match it with finance risk models.
  • There are unique data sources, for example: water availability, soil quality, weather, market movements, satellite imagery, that give a more full picture of the biological process of farming – everything affects the potential future revenue of a farmer, and therefore more sophisticated risk models are needed.

Which Fintech Sandbox Data Partner have you worked with?

We have worked with Equifax, using their Sandbox to explore their credit data and integrating credit reports into the lending workflow, evaluating behavior for ag loan repayment models.

We’ve always had farmers. How can it be that agriculture lending has some of the highest operational costs among the US banking services?

The complexity of the process and the kind of data that is analyzed go beyond financials. There are more variables and more analysis required – doing this in a manual way makes costs high.

Can you describe what it’s been like to be part of the Fintech Sandbox community?

We are supported; we walk along this incredible team that is always there to guide us and support our next phase.

What milestones has Agxes achieved so far?

  • Working with a customer in CA
  • Academic collaboration with Virginia Tech to enhance agriculture- finance ecosystem regionally
  • Main metrics – time reduction, improvement of credit quality

What’s next for Agxes?

  • Farmer’s wallet – financial infrastructure for capital deployment, improve models with more high quality data.
  • Keep growing in partnerships with banking and non-banking financial institutions across the US.

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To hear more about Agxes and five other exciting fintech startups, be sure to register for Fintech Sandbox Demo Day 12!

 

Meet CleverChain.ai — A Demo Day 12 Presenting Startup

Posted on by Jim Smith

This year, Fintech Sandbox Demo Day will take place on Tuesday, April 28. The presentations will be virtual and the event, as always, is free. Demo Days are exciting because we get to showcase startups that are on the very cutting edge of innovation and you get to see what they’re up to before they’re discovered.

Over the next few weeks, we’ll highlight this year’s presenting entrepreneurs. Today, we’re talking to Daniele Azzaro, Co-founder and CEO of London-based fintech CleverChain. CleverChain is a next-generation regtech platform that transforms compliance with AI-driven, real-time, global due diligence and automated risk intelligence. It empowers financial institutions to onboard faster, stay fully compliant, and eliminate manual work with unparalleled speed, accuracy, and scale. CleverChain was ranked 2nd in BusinessCloud’s RegTech 50 for 2025.

Daniele Azzaro, Co-founder and CEO of London-based fintech CleverChain
Daniele Azzaro, Co-founder & CEO of CleverChain

Daniele, tell us a bit about CleverChain. What problems are you solving?

CleverChain is a next-generation regtech platform that transforms how financial institutions perform business due diligence and manage compliance.

Today, compliance teams struggle with fragmented data, manual workflows, slow onboarding, and rising regulatory pressure.

We solve this by delivering AI-driven, real-time global due diligence and automated risk intelligence in a single click. Our technology enables institutions to onboard customers faster, stay continuously compliant, and eliminate huge amounts of manual work without sacrificing accuracy or regulatory confidence.

What is your company’s origin story?

CleverChain was born out of first-hand experience. My co-founders and I spent years building and operating compliance functions inside global financial institutions, and we repeatedly saw the same pain points: disconnected data sources, expensive tools that don’t talk to each other, and analysts wasting time stitching together information. We realized compliance needed a fundamental redesign one that treats data as real-time, connected, and intelligent. That insight became CleverChain.

What problems do financial institutions encounter with compliance data?

The biggest issues are fragmentation, latency, and trust. Data comes from dozens of vendors, arrives in different formats, updates at different speeds, and often conflicts. Teams must manually reconcile everything, which slows onboarding, increases cost, and creates risk. On top of that, regulators increasingly expect continuous monitoring rather than point-in-time checks. Financial institutions need unified, real-time, and auditable intelligence—not static reports.

What were you able to do with the data from the Data Partners you worked with?

We worked with Equifax during our time in the Data Access Residency to access high-quality datasets that allowed us to test, validate, and refine our AI models across global corporate, ownership, and risk data. This access has been invaluable in accelerating product development and strengthening our data orchestration capabilities.

What makes CleverChain different from other AML or KYB solutions?

Most AML and KYB tools focus on running checks. CleverChain focuses on delivering intelligence. We don’t just aggregate data – we normalize, link, and reason over it using AI. Our platform creates a real-time risk graph of companies and people, continuously updating as new information emerges. This means faster onboarding, fewer false positives, and a much richer understanding of risk. We’re also infrastructure-agnostic, so we plug into existing stacks rather than forcing replacement.

EY is a Fintech Sandbox sponsor. What was it like participating in the EY FinTech Growth Programme?

Working with EY through the FinTech Growth Programme was extremely valuable. We gained direct exposure to senior industry experts, refined our go-to-market strategy, and pressure-tested our product positioning with real financial institutions. The programme helped accelerate commercial conversations and sharpen our enterprise readiness.

Can you describe what it’s been like to be part of the Fintech Sandbox community?

It’s been an incredibly supportive and high-quality ecosystem. The community combines startups, data providers, and financial institutions in a way that’s genuinely collaborative. You get fast feedback, meaningful introductions, and access to resources that would normally take years to secure. It’s one of the most practical fintech communities we’ve been part of.

What milestones has CleverChain achieved so far?

We’ve earned the trust of major financial institutions and global enterprises, including top-tier banks and complex, highly regulated organizations across Europe. CleverChain has been recognized as Best KYB product by Chartis Research and ranked 2nd in BusinessCloud’s RegTech 50 for 2025.

More importantly, we’ve crossed a strategic threshold: moving beyond traditional AML and KYB tooling into a new category of autonomous, intelligence-led compliance. Customers are using CleverChain not just to run checks, but to fundamentally change how risk decisions are made—faster, continuously, and at enterprise scale.

What’s next for CleverChain?

We’re building toward a world where compliance operates itself. Our next phase is about delivering fully automated, continuously running risk control—where AI agents monitor, investigate, and resolve risk in real time across customers, counterparties, and transactions.

As we scale globally, CleverChain is evolving into the autonomous intelligence layer that sits at the heart of the financial system, giving institutions live, explainable control over risk at any moment. Not just faster compliance—but a fundamentally safer financial ecosystem.

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To hear more about CleverChain and five additional exciting fintech startups, be sure to register for Fintech Sandbox Demo Day 12!

Meet Gemsen — A Demo Day 12 Presenting Startup

Posted on by Jim Smith

This year, Fintech Sandbox Demo Day will take place on Tuesday, April 28. The presentations will be virtual and the event, as always, is free. Demo Days are exciting because we get to showcase startups that are on the very cutting edge of innovation and you get to see what they’re up to before they’re discovered.

Over the next few weeks, we’ll highlight this year’s presenting entrepreneurs. Today, we’re talking to Charlie Ko, Co-founder and CEO of Boston-based fintech Gemsen. Gemsen is capable of processing massive amounts of data efficiently and securely, producing output that is accurate and in a usable form. Gemsen tames the data deluge using prediction models that require less compute and storage than other technologies.

Gemsen allows organizations to harness the power of machine learning without exposing sensitive data, ensuring complete compliance with data protection regulations. Whether applied within workflows such as insurtech, regtech, fraud detection, credit analytics, compliance, or investment research, Gemsen enables secure collaboration throughout the entire process.

Charlie Ko, Co-founder and CEO of Gemsen
Charlie Ko, Co-founder and CEO of Gemsen

Charlie, tell us a bit about Gemsen. What problems are you solving? What makes your approach different?

Most of today’s advanced technologies are extremely resource hungry. To perform at the speed of current data streams, they often require massive compute and storage in the form of GPU server farms. We took a completely different approach to use math to simplify the computations to what is essential. This not only preserves predictive performance, but also dramatically reduces the required resources by 99% or greater.

What is your company’s origin story?

We are driven by simplicity and elegance. For nearly two decades, our founding team has tackled complex and large-scale data problems by distilling information from noise. We have always understood that data is only useful if patterns can be detected quickly and reliably.

What does it mean to say that you capture the essential statistical structure of data in motion?

When deconstructing the AI/ML models, the functions of these ‘machines’ are distilled into essential equations. Even the most sophisticated models are defined by equations that perform the work of finding patterns. Many models can be simplified. Some models can be captured and interpreted through pre-computations that reflect the inter-relationships of the input data. These relationships can be described via higher and lower order statistical moments. The key is finding the sufficient set of statistics to produce a lossless rendition of the data for the relevant ML models in question.

This essential structure is the key to extremely fast ML training and inference. Additional important outcomes of this design are Gemsen’s adaptability to streaming data, in addition to interpretability and transparency of the models themselves.

Who is Gemsen’s target market?

We target financial institutions that deal with large-scale streaming data volumes each day. Sample institutions include banks, investment firms, brokers, payment processors, and insurance companies. Sample workflows include fraud detection, customer prediction, securities trading, and credit analytics.

Which Fintech Sandbox Data Partners have you worked with?

massive.com provides an extremely rich data set of market flow information spanning many years. Since data is the fuel that powers AI/ML, their clean and reliable data made testing easier for Gemsen. Billions of rows of data flowing at millisecond speed helped us prove our reliability and improve our capabilities.

What milestones has Gemsen achieved so far?

Our software is already enterprise scale and has been deployed in Fortune 100 companies outside finance. There, we have demonstrated substantial increase in efficiency and reliability of the technology. Gemsen was founded to bring this technology to finance and is in active testing within the finance domain.

Can you describe what it’s been like to be part of the Fintech Sandbox community?

It’s been an amazing experience. The people in this community have been extremely giving of their time and expertise. The best part is everyone’s approachability. Coupled with their willingness to share their experience and ideas, this makes a powerful combination.

You also took part in the MassChallenge Fintech Program last year. What was that like?

It was great from the start. The number of conversations and connections from day 1 was extremely important for us to gain quick momentum. I can’t overstate how helpful the entire ecosystem has been for Gemsen. In fact, the connections brought us include two key advisors. Both helped gain resources that are critical in our ongoing work. This is on-top of getting an inside track to Fintech Week and other high-profile events throughout the year, which nets more ideas and connections.

What’s next for Gemsen?

Just spreading the word – that you can tame the data deluge while still being reliable, accurate and efficient.

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To hear more about Gemsen and five additional exciting fintech startups, be sure to register for Fintech Sandbox Demo Day 12!

 

The Q&A from Demo Day 11

Posted on by Jim Smith

Last week, at our 11th Demo Day, we saw five fintech innovators succinctly showcase their solutions to the most pressing challenges in financial services. The companies they founded built these solutions during their recent participation in our Data Access Residency with the support of several of our Data Partners.

The presentations were fast paced, and some of you may have missed the interactions between founders and members of the audience. So, here are a few of the questions audience members asked after seeing what these teams have built, and the answers these founders provided.

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Sandbox Wealth has built a turnkey open banking solution for wealth managers, including independent advisors and family offices, allowing them to offer sophisticated cash management and credit products to their clients. Ray Denis, the Founder and CEO, provided the product demonstration to the hundreds of people who tuned in for Demo Day.

JS: How are you thinking about Agentic AI?

Ray Denis: We’re looking closely at agentic workflows for document ingestion and yield optimization (for both assets and liabilities). Very focused on getting the data layer right before we dive into those features, but it’s a major part of the roadmap.

BC: How are high-net-worth clients onboarded (one at a time or through datasets)?

Ray Denis: We can handle onboarding one at a time or by mass onboarding with an integration to a firm or advisor’s CRM. We let our partners decide how they’d like to address.

BC: Also, how long to integrate for Registered Investment Advisors?

Ray Denis: The process is intended to be quick. After contracting, we can handle the one at a time onboarding almost immediately. I’d budget 60-90 days for mass onboarding to ensure connectivity with the CRM and the accuracy of the data.

Serene is transforming customer care in financial services by helping banks and financial organizations proactively identify, predict, and support customers in vulnerable circumstances. Savannah Price, Serene’s Founder and CEO, provided our Demo Day audience with a demonstration of the capabilities this London-headquartered fintech built while taking part in our Data Access Residency.

SD: What data and systems do you need access to?

Savannah Price: Open banking/ transactional data (current, credit card, savings accounts). Interaction data, voice-to-text (for sentiment analysis).

JB: Who is the end user of Serene? Which business unit of the customer would be the purchaser of this product?

Savannah Price: End user is the financial institution – Heads of Credit Risk, Heads of Collections, Customer Ops. Exploring scam susceptibility use cases at the moment with Fraud/Fincrime teams.

7Analytics has developed AI-driven flood risk modeling for insurers and asset owners, leveraging high-resolution datasets and 600+ physical parameters. 7Analytics can provide crucial information of flood risk, all the way down to the building level. Helge Jørgensen is Co-founder and CEO of 7Analytics, the first insurtech founded in Norway to present at Demo Day.

WC: What is your geographical coverage? Do you have data for commercial and industrial sites? What is the time horizon for your simulations? Which long-term scenarios do you use?

Helge Jørgensen: Yes – we cover commercial sites. We have several industrial customers in the US today that use our technology. Geographical coverage is based on where we see traction. Our technology is scalable, so we are ready to enter new markets.

EM: Are you also considering to expand to the UK?

Helge Jørgensen: We have our technology ready for the UK. We are running several POC in the UK now.

RK: How are your models/products different than First Street?

Helge Jørgensen: Our approach is different in how we are approaching the modeling of flooding. We use high resolution models (3x3ft), high resolution landuse cover, and ML on claims from insurance companies. We provide flood risk covering all flood types – urban, fluvial and storm surge. We also keep our input data up-to-date by using advanced tech for updating/enhancing the terrain and land use data.

Calculum is offering an AI-powered supply chain analytics platform that helps companies unlock working capital, improve supplier intelligence, and generate free cash flow by optimizing payment terms. Co-founder Eric Zager presented Calculum’s capabilities to our Demo Day audience.

JS: Can Calculum help corporates address disruptions in their supply chains caused by tariffs?

Eric Zager: Yes—by leveraging data and benchmarking, Calculum helps corporates negotiate improved payment terms and optimize working capital, providing flexibility to mitigate the impact of tariffs and other cost pressures.

TM: Any intention of supporting your customers on their receivables side, as well?

Eric Zager: Absolutely. While our core focus has been on payables, we’re seeing strong demand on the receivables side and plan to support clients in optimizing their entire working capital cycle.

BL: What are your thoughts about addressing opportunities in supply chain finance yourselves?

Eric Zager: We believe there’s significant potential in integrating supply chain finance capabilities into our platform. While we currently partner with leading providers, we’re actively exploring how we can offer direct solutions to better serve our clients.

Level2 offers the first fully visual no-code systematic trading strategy creation platform built for active traders. Andrew Grevett, Co-founder and CEO, provided a demonstration of the company’s product and an explanation of their B2B2C model. Level2 is making data-driven trading simple and accessible for all.

CS: Does the platform offer any type of education? I understand it enables a lot of resources for traders, but UI seems to assume the user already has a lot of knowledge around trading, and understanding trades.

Andrew Grevett: Yes, education is a key part of our strategy as the visual approach makes learning and understanding simple. It’s something we intend to enhance in the next version, moving more towards a more dynamic approach along with an immersive trading mode.

LZ: Does this include direct feeds (rather than the consolidated SIP tape)?

Andrew Grevett: We do not have any direct feeds at the moment; it’s all from the SIP tape.

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If you’d like to talk to any of these entrepreneurs about what they are building, please reach out to us here. If you weren’t able to attend Demo Day 11, we’ll be posting a recording showcasing the presentations of these five outstanding startups, as well as insights from thought leaders representing the Fidelity Center for Applied Technology, MassMutual, and KKR, to our YouTube channel shortly.

 

Meet 7Analytics — A Demo Day 11 Presenting Startup

Posted on by Jim Smith

This year, Fintech Sandbox Demo Day will take place on April 28. The presentations will be virtual and the event, as always, is free. Demo Days are exciting because we get to showcase startups that are on the very cutting edge of innovation and you get to see what they’re up to before they’re discovered.

Over the next few weeks, we’ll highlight this year’s presenting entrepreneurs. Today, we’re talking to Helge Jørgensen, Co-founder and CEO of Norwegian fintech 7Analytics. 7Analytics develops highly precise predictive models for flood risk for insurers and asset owners.

Helge Joergensen, Co-Founder & CEO of 7Analytics
Helge Joergensen, Co-Founder & CEO of 7Analytics

Helge, tell us a bit about 7Analytics. What problems are you solving?

Floods are frequent and expensive. And this keeps growing. Without much better data people cannot insure their homes and businesses keep their operations going. We provide that data at a much greater granularity.

Why is granularity in flood prediction important and how do you achieve it?

Insurers need to understand flood risk in-depth – property by property. Water moves along the landscape and even a few inches of height difference here or a green spot there makes a huge difference for flood risk. Only the best data tells you the difference in risk from one side of the street to the other.

What is your company’s origin story?

Our founder team built their skills in the offshore oil and gas sector which remains one of the most knowledge intensive industries in one of the toughest environments on Earth. From here a drive to learn and apply the best possible data tool to produce the best possible solutions has led us to flood risk and to breaking away from traditional approaches.

Can you describe what it’s been like to be part of the Fintech Sandbox community?

7Analytics has moved in two dimensions recently and Fintech Sandbox has been an important partner in both consolidating our services to the financial industry and establishing our US organization.

Why is data access important to your startup?

Data is all we do. Much geodata is open source, but we have only made it this far by building partnerships with leading industry players around data access.

What milestones has 7Analytics achieved so far?

Being live on four continents is a major thing that I am super proud of – this includes my own relocation from Europe to Boston and setting up shop here.

What trends in fintech are you most excited about?

Climate innovation has for a long time been very focused on getting emissions down. For good reasons. Now, adaptation is growing in importance and this basically is a matter of risk. Climate risk. And here fintechs play a key part in getting the banks and insurers up to speed.

How does 7Analytics think about leveraging AI in a differentiated way?

AI and Machine Learning is driving a paradigm shift in water risk modelling. The focus is going in a direction of high-quality, rich input data and really understanding patterns and building predictive power. But: many – also insurers – remain anchored in traditional models.

What’s next for 7Analytics?

Kicking in doors to more insurance companies that are realizing that they need much better data to handle the increasing flood risk.

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To hear more about 7Analytics and 4 other exciting fintech startups, be sure to register for Fintech Sandbox Demo Day 11!

 

Meet Calculum — A Demo Day 11 Presenting Startup

Posted on by Jim Smith

This year, Fintech Sandbox Demo Day will take place on April 28. The presentations will be virtual and the event, as always, is free. Demo Days are exciting because we get to showcase startups that are on the very cutting edge of innovation and you get to see what they’re up to before they’re discovered.

Over the next few weeks, we’ll be highlighting this year’s presenting entrepreneurs. Today, we’re talking to Eric Zager, co-Founder of Miami-based Calculum, which is offering an AI-powered supply chain analytics platform that helps companies unlock working capital, improve supplier intelligence, and generate free cash flow.

Eric Zager, Calculum co-Founder

Eric, tell us a bit about Calculum. What problems are you solving?

Calculum is a negotiation intelligence tool that enables corporates to gain a competitive advantage by using advanced analytics and AI to improve payment terms and gather more insights into suppliers. The platform optimizes payment terms with both suppliers and customers – unlocking working capital. The tool also assess suppliers’ ESG, estimated financing costs, credit ratings, negotiation leverage, price vs terms calculator,  along with many other tools that benefit corporate treasury & procurement operations.

What is ADA, and how did it get its name?

ADA is the payment terms platform Calculum has built. It gets its name from Ada Lovelace who is considered the world’s first computer programmer.

Can you describe what it’s been like to be part of the Fintech Sandbox community?

It’s been great to have the support of the Fintech Sandbox and have access to test data from many great companies and sources

Why is data access important to your startup?

Data can be expensive and Calculum requires corporate data in order to provide accurate suggestions to our clients.

What is your company’s origin story?

Calculum was founded in 2020 as a way to benchmark payment terms with suppliers and ensure our client’s suppliers are being offered the correct payment term and to help companies not indirectly finance their competition.

What milestones has Calculum achieved thus far?

Calculum has won several awards including:

  • #1 Florida Early-Stage startup – Florida Venture (Tampa – 2021)
  • Working Capital Innovation Award – Working Capital Forum (Amsterdam – 2022)
  • Procurecon EU Dragons Den Winner – Procurecon (Barcelona – 2024)
  • MassChallenge Finalist – (Boston 2024)
  • Finalist Treasury Innovation Award – TMANY Cash Exchange (New York City – 2024)
  • Supply Chain Finance Innovation Award – Supply Chain Finance Community (Zurich – 2024)

What trends in fintech are you most excited about?

The growing popularity of supply chain finance (Reverse-factoring).

What is the Miami fintech scene like?

Miami’s fintech scene and the overall startup community have grown tremendously since the COVID-19 lockdowns. Many startups began during this period or moved from states like California and New York to the Miami area due to fewer restrictions and a more business-friendly environment.

What’s next for Calculum?

We will be growing our partnerships as well as further developing our solution, in 2025 we will be flipping the model of the tool to also support companies on their receivables side with customers as well.

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To hear more about Calculum and 4 other exciting fintech startups, be sure to register for Fintech Sandbox Demo Day 11!