Investment & Venture
Investment decisions need systematic technical diligence — not one-off reviews.
As deal volume increases, the bottleneck shifts from access to evaluation capacity. Technical due diligence in particular is hard to scale: it requires specialist knowledge, consistent criteria, and auditable outputs that hold up to scrutiny from co-investors and LPs alike.
$2.4B
Global AI in financial due diligence market by 2028
PitchBook Data, 2024
42%
Of PE/VC deals encounter post-close technical issues that were not identified in diligence
Bain & Company, 2023
3×
Faster technical due diligence cycles with automated code analysis vs manual review
CB Insights, 2024
Investment tech diligence maturity
Where most firms stall.
Five stages define the investment technical diligence maturity curve. Most firms only operate in the first two — and wonder why post-close technical surprises keep eroding returns.
Deal sourcing
Pipeline exists but technical quality signal is absent from initial screening
Technical screening
Basic tech stack review but no systematic codebase or architecture assessment
Automated analysis
Repository scanning, code quality scoring, and debt quantification at scale
Risk mapping
Architecture vulnerabilities, key-person dependencies, and scalability risks documented
Continuous monitoring
Post-investment technical health tracking and early warning systems
Failure patterns
Recognise any of these?
Technical due diligence is manual, inconsistent, and produces reports that are outdated before the deal closes
Every deal gets a different reviewer, a different scope, and a different format. The resulting reports reflect individual opinion, not systematic analysis. By the time the document reaches the IC, the codebase has already changed — and the assessment was never comprehensive to begin with.
Investment decisions are made on commercial metrics alone — technical risk is invisible until post-close when remediation costs surface
Revenue growth, unit economics, and market positioning drive deal evaluation. But the technology that delivers those metrics is never stress-tested. Post-close, teams discover architectural limitations, security gaps, and scaling bottlenecks that require unbudgeted remediation — eroding the returns the thesis was built on.
Portfolio companies have no ongoing technical health visibility — problems compound silently between board meetings
After close, technical oversight reverts to quarterly check-ins and self-reported updates. Code quality degrades, technical debt accumulates, and key-person risks grow — all invisible until a production incident, a failed migration, or a down-round forces the conversation.
Code quality assessments vary by reviewer — no standardised rubric produces comparable scores across deals
Without a consistent scoring framework, deal teams cannot compare technical quality across portfolio candidates. One reviewer flags debt as critical; another dismisses it. The result is inconsistent risk pricing and an inability to benchmark across the portfolio.
Data room technical documentation is incomplete or outdated — investors cannot assess what they cannot see
Founders provide architecture diagrams from two years ago, deployment docs that no longer match production, and dependency lists that omit critical services. The data room creates an illusion of transparency while hiding the actual technical state of the business.
Technical debt is discussed qualitatively but never quantified — making it impossible to price into the deal
Diligence reports describe debt as 'moderate' or 'manageable' without attaching estimated remediation costs, timelines, or impact on roadmap velocity. Without quantification, debt becomes a negotiation talking point rather than a financial input to deal structuring.
The gap
Where you are vs where you could be.
Manual expert review with variable scope, inconsistent methodology, and reports that reflect individual opinion rather than systematic analysis
Automated repository analysis with standardised scoring, reproducible methodology, and structured outputs comparable across deals
Qualitative tech narratives describing risk in vague terms — no severity scoring, no remediation costing, no benchmarking
Quantified risk mapping with severity scoring, estimated remediation costs, key-person dependency analysis, and portfolio-wide benchmarking
Weeks of manual review coordinating external consultants, scheduling interviews, and compiling ad-hoc reports
Days with automated analysis, structured reporting, and standardised frameworks that accelerate IC-ready deliverables
Annual check-ins and self-reported updates — technical health is invisible between board meetings
Continuous technical health scoring with degradation alerts, code quality trending, and early warning systems across the portfolio
What we build
The infrastructure your deal team deserves. Engineered.
We build the automated analysis, scoring frameworks, and monitoring systems that investment firms need to move from manual, inconsistent diligence to systematic, scalable technical evaluation — with quantified risk engineered into every deal.
Automated code analysis
Repository scanning, quality scoring, dependency auditing, and vulnerability detection across the target codebase
Technical scoring framework
Standardised rubric aligned to investment thesis criteria — producing comparable scores across deals and portfolio companies
Architecture assessment
Scalability analysis, infrastructure review, security posture evaluation, and production readiness benchmarking
Technical debt quantification
Categorised debt with estimated remediation costs, timelines, and impact on roadmap velocity — priced for deal structuring
Data room structuring
Investor-ready technical documentation, risk summaries, and architecture diagrams that reflect the actual state of the business
Portfolio health monitoring
Continuous code quality tracking, degradation alerts, and early warning systems across the entire portfolio
Start a discovery
Your deal pipeline is growing. Your technical evaluation capacity is not.
A 30-minute diagnostic conversation. No proposal before we understand the system. No commitment before we demonstrate the value.
For investment partners and deal teams
Systematic technical diligence that produces quantified risk assessments, comparable scoring across deals, and IC-ready deliverables — in days, not weeks.
For portfolio operations and technical advisors
Continuous portfolio health monitoring, standardised technical benchmarking, and early warning systems that surface problems before they compound.
Relevant services
Capability areas we most often combine for this context.