Technology Due Diligence

AI-accelerated buy-side and sell-side technology assessments delivered in 1-2 weeks at a fixed fee. The same team that built and exited a tech company evaluates yours.

We deliver AI-accelerated technology assessments in days, not weeks. Our team has advised on $10B+ in capital events, founded and exited a technology company (LexPredict, acquired 2018), and published the empirical research on software ecosystems that underpins modern dependency analysis.

Starting at $30K | 1-2 weeks

How a diligence sprint works

Traditional firms take 6-12 weeks and charge hourly. We deliver the same depth of analysis in 1-2 week sprints at a fixed fee, using AI-accelerated analysis tools we built ourselves — so diligence doesn't hold up the deal.

Traditional Approach vs. licens.io Sprint TRADITIONAL 6-12 weeks, $150K-500K Scoping 2-3 weeks Manual review 2-4 weeks Analysis 1-3 weeks Report 1-2 weeks LICENS.IO SPRINT 1-2 weeks, $30K-80K DAY 1-2 Ingest Code, docs, repos, dependencies, infra DAY 3-5 Analyze AI-accelerated SCA, license, security scan DAY 5-7 Assess Expert review of findings + risk scoring DAY 7-10 Deliver Report, call, recommendations AI-accelerated What we assess: Codebase Dependencies Security Licensing AI / ML assets IP / data Team

Services

Buy-Side Tech Diligence Sprint

Architecture, code quality, technical debt, security posture, IP ownership, dependency analysis, and AI footprint — all in one sprint. Written report with executive summary.

1-2 weeks

AI Footprint Assessment

Inventory all AI in the target: models, training data sources, vendor dependencies, licensing terms, and governance practices. Standard in tech M&A.

1-2 weeks

SBOM & Dependency Analysis

Transitive and cross-language dependency risks. CycloneDX/SPDX generation, quality assessment, and license compliance review.

1 week

Expert Witness

Testimony on software architecture, IP ownership, AI/ML disputes, and technology standards. Published research and 4,000+ academic citations backing opinions.

As needed

Why us

We've built, bought, and sold technology companies

LexPredict: founded, built, exited (acquired 2018). We understand the builder's perspective because we've been there. When we evaluate a target's technology stack, we know what good architecture looks like in practice — and what technical debt actually costs.

Empirical research on software ecosystems

Our published studies on PyPI (178,592 packages) and R ecosystems provide the empirical foundation for dependency analysis. We don't just run scans — we understand how open source risk propagates across software supply chains.

AI tools let us move at deal speed

We built our own analysis tooling — the same kind of AI-accelerated approach we evaluate in targets. That means we can cover more ground in less time without sacrificing depth. PE/VC deal timelines don't wait for consultants — we keep pace.

Why licens.io?

Speed

Big 4

6-12 weeks

licens.io

1-2 weeks

AI depth

Big 4

Adding an AI checkbox

licens.io

Built LLMs from scratch

Experience

Big 4

Advisory only

licens.io

$10B+ capital events, LexPredict exit

Dependencies

Big 4

Generic SCA scans

licens.io

Published ecosystem research: 178K packages

Pricing

Big 4

Hourly, $150K-$500K

licens.io

Fixed-fee, $30K-$80K

Perspective

Big 4

Advisory only

licens.io

Founded, built, and exited a tech company

Who this is for

  • ✓ PE operating partners running buy-side tech DD on acquisition targets
  • ✓ Corp dev teams at strategic acquirers evaluating technology assets
  • ✓ Law firms supporting M&A transactions with technology-enabled diligence
  • ✓ Investors evaluating AI-native targets where traditional tech DD falls short
  • ✓ Companies needing SBOM and dependency audits for compliance or risk management

Frequently asked questions

What does technology due diligence cover in a PE deal?

Architecture review, code quality assessment, technical debt quantification, security posture evaluation, IP ownership verification, dependency and license analysis, team capability assessment, and AI footprint mapping. We cover all of these in a single sprint.

How is AI due diligence different from traditional tech DD?

AI due diligence adds assessment of model architecture, training data provenance and licensing, vendor AI dependencies, model governance practices, and the defensibility of AI-driven revenue. Almost half of recent tech deals have an AI component that requires this expanded scope.

How long does a tech diligence sprint take?

Most engagements complete in 1-2 weeks. We scope tightly upfront, run AI-accelerated analysis in parallel with expert review, and deliver a written report with executive summary. If you have a compressed timeline, we can accelerate further.

What is an AI footprint assessment?

A systematic inventory and evaluation of all AI embedded in a business — models in use, training data sources, vendor dependencies, licensing terms, and governance practices. This is quickly becoming a standard part of technology due diligence in M&A.

How do SBOMs factor into M&A due diligence?

Software Bills of Materials (SBOMs) document every component in a software product, including transitive dependencies. In M&A, SBOMs reveal license compliance risks, security vulnerabilities, and supply chain exposure. EU CRA requirements are making SBOMs mandatory for software sold in Europe, which affects deal structure.

How do you handle compressed deal timelines?

Our AI-accelerated tools and fixed-scope sprint model are designed for deal speed. We have delivered complete diligence reports in under a week when needed. We scope the engagement upfront so there are no surprises on timeline or cost.

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Deal in progress?

We'll assess your target's tech stack, AI footprint, and dependency risk — and give you a written report in 1-2 weeks at a fixed fee.

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