Acquisition intelligence,
built on evidence

Research, screen, and diligence companies with structured data and rigorous analysis. Not opinion. Not guesswork. Evidence at depth.

Explore the platform See the tools
01 — Platform

Tools for every stage of the acquisition lifecycle

From defining your thesis to post-acquisition onboarding. Each app is purpose-built, data-connected, and designed to surface evidence — not generate opinion.

Define Game

Define an acquisition thesis. Set criteria, sectors, geographies, and deal parameters.

Research Game

Deep research on companies within your defined game. Public filings, ownership, financials.

Select Game

Filter, rank, and shortlist. Use our scoring, your own criteria, or third-party rankings.

Screen Companies

Systematic screening against quantitative and qualitative criteria. Pass/fail with evidence.

Do Diligence

Full analysis of public and private data. Evidencing, not opining. Depth matches data depth.

Assess Deal

Investment memo and IC report synthesis. Research + talent + structure + recommendation.

Find Talent

Talent mapping and search. Who runs it, who built it, who left, who's available.

Serial Acquire

Strategy tools for serial acquirers. Portfolio construction, integration playbooks, deal cadence.

Build Archetype

Study and construct serial acquirer archetypes. What pattern fits your thesis?

Observe Competition

Competitive intelligence. Who else is buying in your space, at what pace, at what price.

Map

Geographic mapping of target sectors. Visualise clusters, supply chains, and regional density.

Onboard

Post-acquisition integration. Financial standards, operating playbooks, AI-assisted improvement.

02 — Data

Built on the largest structured UK company dataset we know of

Companies House filings, PSC ownership graphs, employee data, financial metrics — structured, scored, and cross-referenced. Not scraped summaries. Primary sources.

6.8M
Company employee records, scored
10.8M
PSC ownership records, staged
3.2M
UK companies in universe
835
Data dimensions per company
03 — Approach

Evidencing, not opining

Every claim is traceable to a source. Every score is decomposable. Every recommendation shows its working.

Code before tokens

Structured data processing, deterministic scoring, and rule-based filtering happen in code — not in an LLM prompt. AI enters only where judgment is genuinely needed.

Primary sources

Companies House bulk data, PSC registers, published accounts. Not aggregator summaries. Not web scrapes. The filings themselves.

Depth matches data

A diligence report is as deep as the data supplied. Shallow data gets honest uncertainty, not confident hallucination.

Traceable claims

Every assertion links to its evidence. Every score decomposes into its components. No black boxes.