Technical Due Diligence Pre-Read
Before an M&A meeting or partnership evaluation, your agent scans a target's public GitHub repos, tech blogs, engineering job postings, Glassdoor engineering reviews, and conference talks. It delivers a structured technical assessment in 45 minutes so you walk into the meeting already knowing their architecture strengths and red flags.
6-8 hours of manual research before a 1-hour meeting. Most of it wasted.
CTOs asked to evaluate acquisition targets or partnerships spend 6-8 hours researching before a single meeting. Most of that time is manual: scanning GitHub, reading job postings, googling engineering blog posts. You often miss signals because you don't know where to look.
According to Bain & Company's 2024 M&A report, 30% of tech acquisitions underperform because of missed technical debt that should have been caught in due diligence. The research isn't optional. It's just too slow to do by hand.
5 data sources. 45 minutes. No tabs left open overnight.
Give the agent a company name. It scans public GitHub for repo count, language breakdown, commit frequency, star count, contributor patterns, and the ratio of open issues to pull requests. Then it checks job postings — because what roles are open tells you where they're weak.
It also pulls engineering blog posts for architecture decisions and tech stack evolution, filters Glassdoor reviews for engineering-specific feedback on tech debt and tooling, and scans conference talks for what their engineers present publicly. All five sources, cross-referenced into one assessment.
A structured technical profile. Not a wall of links.
The agent doesn't dump raw data. It delivers a structured report covering tech stack profile (primary languages, frameworks, cloud provider, CI/CD), engineering health signals (commit velocity trends, open issue ratio, contributor concentration), and risk indicators.
Red flags get surfaced automatically: high turnover in engineering reviews, infrastructure roles open longer than 90 days, declining commit velocity. Strengths are highlighted too — active open source contributions, growing contributor base, modern stack choices.
Any time you need to know what a company actually built. Not what their pitch deck says.
M&A targets are the obvious one — run the assessment before you spend a full day doing your own research. But it works for partnership evaluations too, before you commit engineering resources to a company whose infrastructure might not hold up.
Use it for competitive analysis when you need to understand a competitor's real technical capabilities — not their marketing. And for vendor evaluation, to check whether their engineering team is actually shipping or whether the product went stagnant two quarters ago.