Industries — Financial Services

Manual synthesis is capping how many deals your team can run.

We build the intelligence infrastructure that automates deal screening, VDR analysis, and deliverable drafting — so your bankers spend their hours on judgment and negotiation, not data extraction.

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The bottleneck

Most of a banker's day is synthesis, not strategy.

High-performing M&A teams are typically bottlenecked by manual synthesis: scanning hundreds of CIMs, normalizing financials from messy data rooms, and drafting repetitive materials. This friction caps the number of active deals per banker — not skill or capacity.

ExecuteML redesigns the deal lifecycle. We treat your firm's knowledge not as static files, but as a retrieval system that actively surfaces insights at the moment they matter.

Where deal time gets lost

CIM & Teaser Review~8 hrs per deal
VDR Document Analysis~2 weeks per deal
Deliverable Drafting~12 hrs per deal
Illustrative averages — 60%+ of banker time on synthesis, not strategy
What we build

Intelligence infrastructure for every stage of the deal.

Built for deal team workflows, not generic document processing.

Automated Deal Screening

Ingestion pipelines that scan news, databases, and inbound teasers to score targets against your specific buy-side criteria — before an analyst opens the file.

VDR Diligence Systems

AI workflows that extract, normalize, and flag risks across large document sets — turning weeks of associate review into focused review-and-verify sessions on what actually matters.

Deliverable Acceleration

Systems that auto-draft substantial portions of Teasers, CIMs, and Market Updates from structured inputs — requiring only editorial refinement from senior bankers.

Impact story

Automating Deal Sourcing

Proprietary deal flow depends on finding targets your competitors can't see. We built a Strategic Intelligence Engine that processed 30M+ US business entities — so deal teams can search by thesis concept and surface off-market opportunities that traditional databases miss entirely.

100x

Targets screened per analyst

30M+

Businesses indexed

Seconds

To a complete tear-sheet

ExecuteML shifted our sourcing from buying stale vendor lists to generating proprietary deal flow. The vector-based engine finds opportunities our competitors simply cannot see with traditional database filtering.

Managing Director

M&A Advisory Firm

Read the full case study
How we work

Deployed in your workflow, not alongside it.

01

Deal Workflow Scoping

We map your current deal lifecycle, identify where synthesis time is being lost, and define the integration points and success criteria before building anything.

02

System Build

We build document ingestion pipelines, AI extraction models, scoring frameworks, and deliverable generation systems — integrated into your actual workflow.

03

Deployment & Enablement

We deploy into your environment, train your team on the new systems, and establish the feedback loop for refining models based on real deal outcomes.

04

Ongoing Improvement

We run 90-day review cycles, refine models based on deal feedback, and extend the system as your sourcing thesis or deal structure evolves.

Uncap your deal capacity.

Tell us where synthesis time is being lost in your deal workflow. We'll scope the intelligence infrastructure and the path to deployment.

Start a scoping call