Generic AI models are incredible reasoning engines, but they are not the best at finance.
If you ask a standard chatbot to summarize a 10-K, it will give you a neat paragraph. But in investment banking and asset management, analysts aren’t looking for neat paragraphs. They are testing complex assumptions, reconciling conflicting premium data sources, and building investment memos that must withstand the absolute scrutiny of regulators and investment committees.
Generic AI delivers speed. It does not deliver trust.
Finster AI is building the intelligence layer that the financial sector can actually rely on.
Founded by Siddhant Jayakumar — who spent seven years building large language models as an AI researcher at Google DeepMind — Finster is an AI-native platform built specifically for financial professionals.
Finster’s core breakthroughs are provenance and personalization. Instead of treating every query the same, Finster learns how an individual analyst works. One user might need exhaustive downside risk scenarios with deep citations, while another needs a tight, client-ready narrative. Finster adapts to these workflows, securely fusing public filings with a firm’s internal historical analyses and proprietary deal logic. Most importantly, every single number it generates is instantly auditable and hallucination-free.
The market? The massive global asset management and investment banking industry that wants the leverage of AI but cannot afford the compliance nightmare of generic models.
Siddhant and his team are proving that true enterprise AI isn’t just about building a bigger model; it is about building a domain-specific brain.
Let’s celebrate the builders.
w/ Jay Ingle & Dikshant Joshi
#FinTech #EnterpriseAI #AIBoomiAnnual26
