A running Claude session watches a live diagram, reads freehand annotations against it, and rebuilds the artifact on the spot.

A framework to select the simplest, fastest, cheapest architecture that will balance LLMs’ creativity and risk

LLMs write investment memos that sound right but aren't optimal. They sample from a distribution of plausible analyses rather than reasoning within your firm's proven methodology, quietly commoditizing your decision-making and masking your associates' real analytical judgment. To preserve alpha, don't buy generic tools. Build custom agentic workflows anchored by your firm's proprietary POV, deterministic verification, and iterative refinement, so AI drives optimal decisions instead of articulate guesses.

Financial regulators are reshaping enterprise AI purchasing decisions – here's why and what organizations must do to satisfy evolving governance expectations.

Most AI products succeed or fail based on orchestration, controls, and trust-building mechanisms that shape behavior, reliability, transparency, and user confidence.

Top takeaways from an exclusive NY Tech Week panel with operators from JPMorgan Chase, Apollo, and Google Cloud on building enterprise AI that ships, scales, and survives a regulator's review.

This is part two of a two-part blog adapted from my conversation with Marc Andrew on Modern Capital: The Private Markets Podcast.

This is part one of a two-part blog adapted from my conversation with Marc Andrew on Modern Capital: The Private Markets Podcast.

A look at why embedded AI consulting models may recreate the same scalability and lock-in problems financial institutions have faced with legacy enterprise software and system integrators.

Obin AI’s Context Studio transforms document AI from fragile experimentation into a structured, version-controlled engineering workflow for financial institutions.

A Cornell workshop shows how AI is rapidly reshaping finance careers, forcing the next generation to shift from doing analyst work to building and overseeing intelligent systems.

Obin AI’s platform enables financial institutions to deploy a production-ready agentic workforce on Google Cloud

Obin improved on a reactive AIMD rate limiter with a hybrid latency-adaptive strategy. When making LLM calls at scale, proactively adjusting concurrency based on API response times achieved 7x throughput and 98% fewer errors in our distributed document-processing pipelines.

Backed by Motive Partners and AI pioneers Dr. Fei-Fei Li and Lukasz Kaiser, Obin AI is closing the gap between AI potential and regulated deployment — already trusted by firms managing over $1 trillion in assets under management.

Why do most AI pilots in finance fail while a few actually scale? This post uncovers the hidden infrastructure and domain expertise needed to move from impressive demos to reliable, production-ready AI, and explains why finance demands far more than “mostly correct” models or better prompts.

The founding story of Obin AI