Amit Chatterjee

Enterprise AI, from someone
who ran the systems.

I'm a Wall Street technology leader turned AI practitioner. I help banks, funds, and investors separate what actually works in enterprise AI from the noise — grounded in 35 years building the trading, risk, and data systems capital markets run on.

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35+ years on Wall Street U.S. Bank Citigroup Weeden & Co. CTO / CIO NASDAQ Tech Advisory Committee
Work with me

Three ways I help

I work with a small number of organizations at a time — as an outside expert, not an employee. If you're trying to make a real decision about enterprise AI, I bring an operator's judgment, not a vendor's pitch.

Expert calls

A practitioner's read, on the record

For expert networks, institutional investors, and diligence teams who need a grounded view of enterprise and capital-markets AI — where it's real, where it's hype, and what it means for a business or a thesis.

Expert networks · investors · diligence
Advisory & fractional

From AI strategy to what deploys

Hands-on advisory for banks and financial firms: cutting through the hype to what actually ships, what it costs, how it's governed, and where build-vs-buy really lands — from someone who has run production systems under a compliance regime.

Banks · funds · fintechs
Speaking & panels

Talks that cut through the noise

Keynotes, panels, and moderated sessions on enterprise AI in regulated industries — the economics, the governance, and the operating reality of putting AI into a financial institution.

Conferences · panels · private events
Writing

Inside Enterprise AI

I write in public — a practitioner's perspective on AI, cloud, and technology transformation, and the economics of making them work inside real enterprises.

The newsletter

Inside Enterprise AI

Every issue is grounded in real-world implementation — what actually works, what it really costs, and how it gets governed inside a financial institution. No hype, no theory. Just the view from someone who has built and run these systems.

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Latest · Inside Enterprise AI · August 11, 2026 · 6 min read

The AI Infrastructure Gold Rush: Who Ultimately Pays the Bill?

Nvidia and the hyperscalers are deploying hundreds of billions into AI infrastructure. But someone ultimately has to generate the return — a practitioner's view on the total cost of enterprise AI, and who captures the value.

Read the post

The full archive lives here on my own site, not just on LinkedIn. See all writing →

Expertise

What I go deep on

Three decades across the technology that capital markets depend on — now focused on making AI deployable inside it.

Enterprise AI

AI adoption strategy The economics of AI Build vs. buy AI governance Grounded & auditable AI Agentic systems

Capital markets

Trading systems Market data Risk technology Equities & execution Regulatory & compliance tech

Enterprise technology

Cloud migration at scale Technology due diligence M&A integration Modernizing legacy systems Engineering leadership
Proof of work

I don't just advise on this — I build it

The fastest way to know someone understands enterprise AI is to see what they've shipped.

PRISM

A governed AI-agent platform for capital markets

I built PRISM to prove the thesis I advise on: that AI becomes deployable inside a financial institution only when it's grounded in real sources, cited, auditable, and kept under human review. It turns scattered public data — SEC, FINRA, the Fed — into cited, checkable answers.

  • Cited Q&A and PM-ready memos over 166,000+ SEC filings
  • Every claim traced back to its source document
  • Governed, entitlement-aware, and fully auditable
See PRISM at traccg.com
166k+
public filings made answerable — with a citation behind every line.
About

An operator, not a spectator

Amit Chatterjee

Amit Chatterjee

Enterprise AI Advisor · Founder, TRAC Consulting Group

Over more than three decades on Wall Street, I designed, built, and ran the trading, market-data, risk, and operations technology that financial institutions depend on — most recently as Head of Enterprise Cloud Migration & Capital-Markets Technology at U.S. Bank, and earlier as CTO of Global Equities Technology at Citigroup and CIO at Weeden & Co. I've also served on the NASDAQ Technology Advisory Committee.

I now bring that operator's perspective to enterprise AI — helping teams adopt it the way I'd have had to defend it myself: grounded, governed, and economically real.

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Let's talk

Expert-network calls, advisory and fractional work, or a speaking invitation — tell me what you're working on and I'll get back to you.

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