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

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.

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.

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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, 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.