Industries — Financial Services

AI agent infrastructure for fintech teams past the pilot phase.

We build the compliance, risk, and data infrastructure that replaces manual bottlenecks — so your team handles more volume without adding headcount. Scoped to your stack, tracked from day one.

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The problem

Where fintech operations stall.

The bottlenecks are predictable. The cost is real. Most teams try to hire their way through them — until the queue outpaces the headcount.

01

KYC/AML queues that grow faster than your compliance team can clear them

02

Entity data spread across five systems that never fully agree

03

Reconciliation exceptions that need manual investigation every cycle

04

Credit underwriting that takes days when it should take hours

What we build

Production systems for fintech operations.

Purpose-built for the data complexity and compliance requirements of financial services.

Compliance & Risk Operations

We build automated KYC/KYB workflows and AML case triage systems with human-in-the-loop controls. Your compliance team reviews decisions — not raw data — while throughput scales without headcount.

Business Intelligence Infrastructure

We build the entity intelligence layer that powers underwriting, onboarding, and risk decisioning — processing millions of records and returning structured, decision-ready profiles in seconds.

Financial Operations (FinOps)

We automate reconciliation matching and exception routing so your FinOps team handles edge cases, not routine transactions. Pipelines connect across banks, processors, and ledgers — with intelligent routing where human review is warranted.

Credit & Underwriting Systems

We extract structured data from financial documents, automate risk scoring, and surface decision-ready intelligence for your underwriters — reducing cycle time without reducing control.

Impact story

Automating Strategic Intelligence

Manual target screening was limiting how many deals a firm could review. Analysts spent days on research just to build basic target lists. We built a Strategic Intelligence Engine that processed 30M+ US business entities — letting bankers ask complex thesis questions and get fully enriched tear-sheets in seconds.

100x

Targets screened per analyst

30M+

Businesses indexed

Seconds

To a complete tear-sheet

ExecuteML automated our entire first-pass diligence layer. Our deal teams now screen 100x more targets without adding headcount. The intelligence engine has fundamentally changed how we source opportunities.

Managing Director

M&A Advisory Firm

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How we work

From scoping to production in defined cycles.

01

Workflow Scoping

We map your operations to identify the manual workflows creating the most friction — and define the success criteria before any code is written.

02

Design & Specify

We design the agent's actions, integration points, and human-in-the-loop controls against your real systems, data, and compliance requirements.

03

Build & Deploy

We build, test against edge cases, and ship to production in weeks — with monitoring and observability built in from the start.

04

Track & Iterate

We measure performance in production and run 90-day review cycles to improve, extend, or address any shifts in system behavior.

Build the infrastructure your operations actually need.

Tell us which workflow is creating the most friction. We'll map an integration and a path to production — with defined milestones and tracked outcomes from day one.

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