Global Fintech Fest 2026
OriginChainDB took the stage at India's largest gathering of the people shaping finance, to show what an AI-native multimodal database looks like in practice.
AI has changed what teams ask of a database. One request often has to look up structured records, search across documents, find similar embeddings and follow the relationships between entities. Most teams run a separate system for each of those shapes, then spend most of their effort keeping the copies consistent. That is where AI projects slow down, get expensive and lose the confidence of the business.
Agents make it harder. An agent does not only read data, it acts on it, so the data layer has to hold its state, record where every answer came from and keep up with live context. In regulated industries such as banking and capital markets, all of that also has to stay inside the right region and remain auditable.
A multimodal database answers this by putting every query shape on one atomic store: SQL, vector search, full-text, graph and plain-English questions over one engine, one copy of the truth, and one place to secure and govern it. We think that is the foundation the next generation of AI applications in finance will be built on.
Thank you to the organisers for the platform, and to everyone who came to the session. If you are building AI products in fintech and want to go deeper, we would like to hear from you.
