Most technical due diligence is a consultant interviewing the CTO for three days. We analyze the software itself — every commit, every dependency, every decision trace — and hand you evidence, not a summary of what you were told.
Technical due diligence — sometimes called software due diligence or engineering due diligence — is an independent assessment of a software asset's real condition. The baseline is a code review: does the code have violations, and does it meet the compliance it should? That matters — but the code, examined by itself, can't answer the questions that actually decide a deal:
Those answers don't live in the source alone. They live in the commit history, the tickets and PRDs, and the people who made the decisions. So we audit the whole system — the code, the decisions that shaped it, and the knowledge holding it together — and you leave understanding not just what the software is, but why it became that way.
The baseline: does the code meet the standards and regulations it claims? We surface security vulnerabilities, business-logic flaws, GDPR and SOC 2 exposure, and audit-trail gaps via Code Property Graph analysis — from the code, not a questionnaire.
How far has the built system diverged from what was specified? We compare PRDs to tickets to commits to the code that shipped. The gap between stated intent and actual implementation is where surprises live.
Who owns what — and what happens when they leave? Git-history analysis finds the developers who hold unique expertise over critical subsystems. A bus factor of one on a revenue-critical module is a material risk, quantified by component.
Will it support the growth thesis? We map the real system topology, not the aspirational diagram, and identify the coupling, bottlenecks, and single points of failure that bite when you push past today's scale.
Will you have issues running it? Deployment history, failure modes, and operational debt — the difference between software that demos and software that runs reliably once it's yours.
What do you actually own? Every declared and undeclared dependency, with copyleft contamination and AGPL exposure flagged. Source is processed in isolated environments under full confidentiality.
Not all debt is equal. Change-driven prioritization surfaces the code that is both complex and frequently modified — where maintenance cost and delivery risk actually concentrate.
What would it cost to rebuild this from scratch today? We normalize total code volume to person-years and separate genuine custom IP from open-source and boilerplate.
We connect to repos, CI/CD, and infrastructure under NDA in an isolated environment. The target's team keeps shipping; nobody's workflow changes.
Our tooling builds the knowledge graph — every entity, relationship, and decision trace — plus dependency mapping and industry benchmarking. Automated, not interviews.
Consultant review, story synthesis, and an executive briefing. Deliverables formatted for an investment committee or board.
Formatted as five stories — each answering one question the deal team needs resolved — backed by the supporting evidence below.
Our standard engagement runs two weeks, built for deal speed: read-only access and NDA in week zero, automated analysis and knowledge-graph construction in week one, and consultant synthesis plus an executive briefing in week two. We operate under data-room restrictions and accelerated schedules when the deal demands it.
A traditional consultant interviews the team and reviews documentation, then writes up what they were told. We analyze the code, commit history, and dependencies directly — so the findings are reproducible evidence, not a synthesis of self-reported claims.
Five stories formatted for investment-committee consumption, plus a prioritized risk map, compliance readiness by framework, a dependency and license audit, a key-person dependency map, and strategic options with effort and trade-offs. You also keep a searchable knowledge base of the system.
No. The same analysis serves acquirers and investors during diligence, CTOs who inherited a codebase, and operators preparing a company for sale. The lens changes; the underlying evidence doesn't.
A thorough technical due diligence checklist covers eight areas: compliance and security violations, requirements drift, ownership and knowledge concentration, amenability to expansion, operational reliability, IP and open-source risk, technical debt hotspots, and cost-to-replicate. We assess every item from the code, commit history, and dependencies directly — not a questionnaire — so each line of the checklist is backed by reproducible evidence.
What We Are Not
We don't write code, manage your engineering team, or sell you a transformation roadmap. Our only interest is an accurate picture — which is exactly why you can trust it. What happens next is your decision, made with the right information for the first time.
Two weeks. One investment. Complete technical clarity before you sign.
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