Capital Markets Technology

Applied AI for Capital Markets

TRAC builds vertical AI systems that financial institutions can actually deploy — domain-grounded, governed, auditable, and human-in-the-loop.

Built for the realities of trading, operations, risk, and regulatory workflows.

Every firm is adopting AI. Few can deploy it where it matters.

In capital markets, the hard part isn't the model — it's making AI safe to run against trade data, operations, risk, and regulatory workflows. That's the gap TRAC builds for.

Vertical, not general

Domain-grounded by design

General copilots don't understand filings, trades, settlement, or risk. Our systems are built around the workflows analysts and operations teams actually run.

Governed, not experimental

Controls before autonomy

Institutions need identity, entitlements, audit, and human oversight before AI touches production. Governance is a first-order feature, not an afterthought.

Deployable, not demo-ware

Survives CTO & compliance

Runs in your environment, your security posture, your review process. We design for the last mile — the part that decides whether AI ever reaches production.

What we build

A focused portfolio of vertical AI systems for financial institutions — each shaped with the firms that use it.

Live

PRISM

The Diligence Engine

A vertical AI co-pilot that automates the first pass of investment due diligence — extracting, normalizing, and summarizing SEC filings into a PM-ready memo, without automating the decision.

  • Deterministic first-pass workflow across filings, decks, and transcripts
  • Every claim linked to source text; full audit trail
  • Client-owned AWS or managed single-tenant deployment
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New · Built per client

AI Agents for Capital Markets

Operations & investigation agents

AI agents that take on the repetitive investigation work in capital-markets operations — trade reconciliation, settlement fails, and exception handling — under human oversight and full auditability.

  • Targeted at breaks, fails, and exceptions across the trade lifecycle
  • Start from accelerators, then customized to your systems and policies
  • Human-in-the-loop and audit-ready by design
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The TRAC approach

The same principles run through everything we build. They're what make AI trustworthy enough to put into production at a financial institution.

Human-in-the-loop

Systems run the repetitive work; people keep judgment and accountability. Nothing high-impact happens without review.

Vertical & grounded

Built around real capital-markets workflows and data — not a general chatbot with a finance prompt bolted on.

Auditable by design

Every step — ingestion, extraction, transformation, override — is logged, attributable, and ready for examination.

Client-owned & secure

Deploy in your own AWS or a dedicated single-tenant instance. Your data stays isolated; we support the machine, not the investments.

How we work: design partnership, not a vendor pitch

We build with a small number of institutions rather than selling to many. A staged engagement where each phase produces something real and an explicit decision to continue.

1

Discovery

Align on the workflows, systems, and governance requirements that matter most in your operation.

Weeks 1–4
2

Build

Stand up a working system against one real workflow, in an environment that fits your security posture.

Weeks 5–12
3

Pilot

Run it with real users and data under supervision; measure the impact and harden the controls.

Quarter 2
4

Scale

Extend to additional use cases, systems, and teams under a roadmap shaped together.

Beyond
Who we are

Built by people who ran the technology

TRAC was founded by senior Wall Street technologists who spent decades building and running the trading, market-data, risk, and operations systems that capital markets depend on. We've sat in the CTO's chair and been through the compliance review — and we build accordingly.

Amit Chatterjee

Founder

  • Former Managing Director & CTO, Global Equities Technology — Citigroup
  • Former Managing Director & CIO — Weeden & Co.
  • 25+ years building trading, market-data, risk, and operations technology on Wall Street
  • Led technology diligence and integration across multiple capital-markets M&A transactions
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Perspectives

How we think about AI in capital markets — workflow, auditability, governance, and institutional advantage.

Thesis

The Alpha Bottleneck

Why first-pass automation, not data or capital, is the real constraint in fundamental investing.

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Governance

Co-Pilot, Not Auto-Pilot

Why human-in-the-loop and auditability are mandatory for AI in regulated research.

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Architecture

Client-Owned AI

Why infrastructure ownership matters when AI touches sensitive institutional data.

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Whether you're exploring PRISM, interested in AI agents for your operations, or want to scope a project — tell us what you're working on.