Available at diligence · before you sign

Integration intelligence that reads the deal — not just the documents.

Detailed integration advisory before the decisions that determine returns have been taken.

Senior integration analysis typically arrives weeks after signing — when the retention windows have passed, the governance asks weren't in the SPA, and the architecture decisions got deferred to Day 1. Integration Intelligence changes that.

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The timing problem

Integration advice early enough to make a difference.

The integration questions that matter most — who leads the programme, which systems survive, where the key person risk sits — all have windows. Those windows are at diligence and signing, not Day 30.

Traditional integration advisory

Delivered weeks post-close

Retention windows already closed

Architecture decisions already deferred

Governance asks weren't in the SPA

Board briefed after commitment, not before

Integration Intelligence

Produced at diligence or signing stage

Retention packages flagged before announcement

Architecture decisions on the pre-close checklist

Governance requirements in the IC paper

Board engaged with execution risks before they commit

Example — Project Aurora

The engine identified that the Year 2 technology migration was already at risk before signing — based on a finding buried in the due diligence pack. Surfaced at diligence, that is a renegotiation point. Surfaced at Day 30, it is a problem.

As early as diligence

integration intelligence available from the moment you have deal documents

200+

analytical signals, patterns & rules evaluated on every deal

Any volume

2 documents or 20 — the engine reads everything you have

20yrs

of delivered integrations encoded in the system

Engine output

Project Aurora — illustrative output

A £355m geographic expansion acquisition. Five source documents into the engine. Below is a sample of what was produced.

Overall integration confidence

Cautious — Intensive execution tier

11.6x EBITDA · £355m · Geographic Expansion

This is a geographic gap-fill at premium price — a PE-backed growth platform paying 11.6x earnings for continental European market access it could not build organically, with a £24m synergy programme that must land within a 3–5 year exit window. The cost synergy case, independently validated, provides a defensible floor: at 100% delivery it alone produces a satisfactory return on the acquisition price. The revenue synergies are genuine upside, not base case. The primary confidence risk is that the programme has not been resourced to execute what the thesis requires: management is thin and managing a concurrent international expansion, no Integration Sponsor has been appointed, and the pre-close planning infrastructure is materially incomplete.

Project Aurora is a fictional transaction created to demonstrate engine capabilities. All company names, financial figures, and individuals are illustrative.

The operator angle

Why not just ask a general AI?

You can. You'll get a reasonable read and generic risk frameworks — analysis calibrated to what sounds right.

What you won't get is output grounded in what actually fails. The failure signatures, the pre-close flags, the governance asks that boards actually need — these come from delivered integrations, not from training data. The AI structures and scales the judgement. The judgement itself is the product.

risk patterns

Built from real M&A failure modes — not generic frameworks

deal states

Combinations of signals that define how a deal will behave in execution

200+

analytical elements

Signals, composites, risks, and decisions evaluated on every deal

Process

From documents to advisory output

A structured analytical process, reviewed by a senior practitioner before delivery. Every output is traceable to a source document.

Share your deal pack

IC paper, board pack, FDD, synergy model, management presentations. Secure, confidential, isolated per deal.

Deep document analysis

Every document is read in full. Signals, contradictions, and gaps are identified across 16 analytical domains. Nothing is skimmed.

Integration pattern matching

The analysis runs against risk patterns, deal states, and governance requirements built from real delivered integrations — not generic frameworks.

Practitioner review and output

A senior practitioner reviews the full analysis before delivery — a board report and management blueprint, written at the level of senior advisory.

Confidentiality

Deal documents are processed in isolated environments. Each deal is stored under a unique identifier — company names never appear in storage paths.

Data security

Encryption at rest and in transit. Access-controlled per deal. Immutable audit log on every operation. No deal data is used for model training.

Deployment

Flexible deployment options under development including private and enterprise configurations for organisations that cannot use public AI tooling on sensitive materials.

About

Built by someone who has done it

Jon Milsted has spent 20+ years personally delivering integrations — at GoCardless, OVO Energy, Mastercard, and Deloitte. Not advising on them. Delivering them.

The patterns in the engine — how deals fail, what boards miss, where execution falls apart — come from that delivery experience. Integration Intelligence combines that judgement with AI to make it available at the point in a deal when it actually changes outcomes.

£100m+

run-rate savings delivered

8,000+

FTE integrations led

£60m

annual loss turned to profitability

Get access

Request a pilot

We're running a limited pilot with PE firms and corporate M&A teams. If you have a live deal or a recent transaction you'd like to test the engine on, get in touch.