Institutional AI · Financial Services

Institutional AI for the firms that move markets.

We've spent 20+ years inside hedge funds, banks, and financial infrastructure firms. We know where the friction lives — and we build AI that eliminates it.

20+
Years Institutional Finance
10+
Institutions
30+
Engineers
5
Products

Where We've Been

We've been inside the firms you run.

Our team has operated inside institutional trading desks, compliance functions, quant research teams, and operations at firms across the buy-side and sell-side. That's not a selling point. It's why we know what to build.

Coverage

Bulge bracket banksSystematic hedge fundsAsset managersMarket infrastructure
OTC Markets
MLops · NLP-to-SQL · EDGAR/XBRL
Société Générale
Algo trading
Quest Partners
Systematic strategies
StoneX
Institutional financial services
Hudson Bay Capital
OMS implementation
T. Rowe Price
OMS implementation
Sapient
Financial technology consulting
Open Link
Energy & commodity trading tech
Triple Point Technology
Commodity management
ION
Trading & workflow automation
Morgan Stanley
Institutional trading

What We Build

Production-grade AI for institutional finance.

Not proof-of-concepts. Not demos. Systems that run in production — with audit trails, human-in-loop controls, and the compliance architecture institutional clients require.

Every system includes

Full audit trailsHuman-in-loop controlsCompliance-ready architecture

TAE Signals

Live

Automated quant and trading intelligence.

Real-time market signal generation, algo strategy execution, and market data pipelines. Built by quant practitioners, running in production.

Quant funds · Systematic hedge funds · Prop desks

FinAgent

Agentic AI pods for institutional workflows.

Planner → Researcher → Executor → Auditor architecture on AWS Bedrock. Human-in-loop via return-of-control. Full reasoning traces for compliance and audit.

COOs · CROs · CCOs at mid/large funds

FinQuery

Natural language to SQL for financial data.

Query positions, P&L, risk exposures, and trade history in plain English. Built on production NLP-to-SQL with EDGAR/XBRL taxonomy expertise.

Portfolio managers · Analysts · Risk teams

RegGuard

AI-powered compliance automation.

Form PF data assembly, communications surveillance triage, DDQ response automation, and regulatory change monitoring.

CCOs · Outsourced compliance firms · COOs

FlowDesk

OMS/EMS implementation and AI automation.

FlexTrade and Charles River deployments. Prime broker connectivity. The OMS/EMS swivel-chair problem solved — with intelligent routing and TCA on top.

Heads of Trading · COOs at mid/large funds

How We Engage

Consulting first. Product when it fits.

Every engagement starts with a scoped pilot — real deliverable, real deadline, real fee. We don't do free POCs. We've done this work before; we know how to scope it tightly and ship.

Engagement model

Scoped PilotBuildRetainer

AI Agent Design & Deployment

End-to-end agentic pod build on AWS Bedrock. Human-in-loop controls, audit trails, compliance architecture included.

Target: COO / CTO

OMS Implementation

FlexTrade or Charles River deployment, prime broker connectivity, EMS integration. Migration consulting for Enfusion and Eze transitions.

Target: Head of Trading / COO

Data Intelligence Build

NLP-to-SQL pipeline, EDGAR/market data integration, financial data lake architecture. Ask your data in plain English.

Target: CTO / Head of Data

Compliance Automation

Form PF data assembly (Oct 2026 deadline), DDQ automation, communications surveillance triage, regulatory change monitoring.

Target: CCO

Operations Automation

Reconciliation break classification, corporate action processing, shadow NAV automation. The daily grind, eliminated.

Target: COO / CFO

IR Workflow

DDQ response system, investor letter drafting, CRM relationship intelligence. 20–40 hours per DDQ reduced to 2–4.

Target: Head of IR

Why Us

Veterans. Not vendors.

PRACTITIONER-BUILT

We've sat at these desks.

We've run OMS implementations. Sat in compliance reviews. Debugged reconciliation breaks at 7am before market open. The AI we build reflects that — it solves the right problem, not the obvious one.

SHIPS TO PRODUCTION

Not decks. Working systems.

TAE Signals is live. The NLP-to-SQL pipeline we built at OTC Markets processes real financial data. We have a bias for working systems over impressive presentations.

SCALED CAPACITY

30+ engineers behind every engagement.

We have data engineers, AI/ML specialists, trading systems developers, and cloud infrastructure architects ready to execute — not just advise.

Team

Built by operators.

We didn't study institutional finance. We worked in it — across trading desks, compliance functions, quant teams, and operations at firms that collectively manage trillions in assets.

40+

Years Combined

12+

Institutions

30+

Engineers

AG

Aman Grover

Co-founder

Experience across OTC Markets, Sapient, ION, Open Link, and Triple Point Technology. Built production MLops, NLP-to-SQL pipelines, and agentic AI systems for financial data at scale.

Co-founder: Brandspeak.ai · TradeAiEdge

AG

Anu Grover

Co-founder

OMS implementation lead at Hudson Bay Capital and T. Rowe Price. Algorithmic trading background at Société Générale. Experience across StoneX, Open Link, Quest Partners, and Morgan Stanley. Deep hands-on experience deploying and operating institutional trading infrastructure across buy-side and sell-side environments.

Co-founder: TradeAiEdge

Common Questions

What funds ask us.

Questions we hear from COOs, CCOs, and Heads of Trading evaluating AI for their firms.

Contact

We work with a small number of clients at a time.

If you're evaluating AI for your fund, operations team, or compliance function — and you want to talk to people who've done this work before — reach out. No pitch deck. Just a conversation.

Emailfounder@tradeaiedge.com
LocationNew York, NY
Schedule a 30-min Call →

What to expect

No pitch deck

We talk to understand your problem first. If we can't help, we say so.

Scoped proposal in days

Not weeks. We've scoped and priced these engagements before — the process is fast.

Real deliverables from day one

Every engagement starts with a pilot that has a concrete, measurable output.