Engineering team intelligence for M&A and risk analysis

Engineering Team
Intelligence
for M&A Due Diligence

ContributorIQ analyzes GitHub commit history to identify key person dependencies, quantify bus factor risk, and surface subject matter experts. This gives private equity firms, venture capitalists, and engineering leaders the technical due diligence data they need to make confident investment and talent decisions.

Trusted by engineering teams worldwide

Everything you need to understand your team

Deep insights into code contributions, commit patterns, and team dynamics across all your repositories.

Contribution Analytics

Track commits, lines changed, and files touched. See exactly who's driving progress across your codebase.

Subject Matter Experts

Automatically identify domain experts for each repository based on contribution history and code ownership.

Multi-Repo Audits

Analyze your entire organization at once. Get a unified view of contributions across all repositories.

Time-Based Filtering

Filter contributions by time period to understand recent activity, quarterly performance, or historical trends.

Identity Merging

Consolidate contributor identities when developers use multiple emails or names across commits.

Secure GitHub App

Read-only access to your repositories. We never store your code, only the commit metadata we need.

Built for Critical Business Decisions

Whether you're evaluating an acquisition, conducting performance reviews, or planning for key departures, ContributorIQ provides the data you need.

M&A Technical Due Diligence

Before closing an acquisition, understand the true health of the target's engineering organization. Identify key person dependencies, orphaned code with no maintainer, and retention risks that could derail post-merger integration.

Learn more about M&A due diligence

Engineering Performance Reviews

Move beyond subjective assessments with quantitative contribution data. Understand who your top performers are, who is ramping up, and who may be disengaging, all backed by commit-level analysis.

Learn more about performance analytics

Departure Risk & Succession Planning

When a key engineer gives notice (or before they do), know exactly which repositories and systems are at risk. Prioritize knowledge transfer and identify internal candidates for succession.

Learn more about departure planning

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Frequently Asked Questions

Learn more about how ContributorIQ analyzes your engineering organization.

What is bus factor analysis?

Bus factor (also known as truck factor or lottery factor) measures how many team members would need to leave before a project stalls due to knowledge loss. ContributorIQ calculates bus factor using Degree of Authorship (DOA) analysis, which considers who created files, how often contributors modify them, and how knowledge decays over time. A bus factor of 1 indicates critical risk, meaning a single departure could stall the project.

How does ContributorIQ identify subject matter experts?

ContributorIQ uses Degree of Authorship (DOA) analysis based on the Fritz et al. research model to identify subject matter experts. This approach considers three factors: whether a contributor created a file (First Authorship), how many times they've modified it (Deliveries), and how much the code has changed since their last contribution (Acceptances). Contributors with DOA scores above 0.75 are considered file "authors" with deep expertise.

Is ContributorIQ suitable for M&A due diligence?

Yes. ContributorIQ is specifically designed for M&A technical due diligence. It reveals hidden concentration risks that financial audits miss, such as critical systems depending on one or two developers. The platform provides Organization Health Scores, bus factor analysis, orphaned file detection, and contributor lifecycle classification to help acquirers understand post-deal technical risk.

What data does ContributorIQ access from GitHub?

ContributorIQ uses read-only access to your GitHub repositories through a secure GitHub App installation. We analyze commit metadata only, including author information, timestamps, and lines changed. We never store your source code, commit messages, or file contents. When generating AI-powered summaries, only anonymized aggregate statistics are sent to AI services.

How is the Organization Health Score calculated?

The Organization Health Score (0-100) combines four equally-weighted factors: Bus Factor Score (based on DOA-calculated bus factor), Single Author Score (penalizes files with only one significant author), Gini Score (measures how evenly commits are distributed), and Activity Score (based on recent contributor activity). Higher scores indicate better knowledge distribution and organizational resilience.

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