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.
Deep insights into code contributions, commit patterns, and team dynamics across all your repositories.
Track commits, lines changed, and files touched. See exactly who's driving progress across your codebase.
Learn more →Automatically identify domain experts for each repository based on contribution history and code ownership.
Learn more →Analyze your entire organization at once. Get a unified view of contributions across all repositories.
Learn more →Filter contributions by time period to understand recent activity, quarterly performance, or historical trends.
Learn more →Consolidate contributor identities when developers use multiple emails or names across commits.
Learn more →Read-only access to your repositories. We never store your code, only the commit metadata we need.
Learn more →Whether you're evaluating an acquisition, conducting performance reviews, or planning for key departures, ContributorIQ provides the data you need.
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 diligenceMove 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 analyticsWhen 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 planningConnect your GitHub organization and get insights in minutes. No credit card required.
Start analyzing for freeShort, citable definitions of the core ideas behind engineering team intelligence.
Bus factor is the minimum number of engineers whose departure would stall a software project due to knowledge loss. A bus factor of 1 means a single resignation, illness, or competing offer can halt development on a critical system. ContributorIQ calculates bus factor using Degree of Authorship (DOA), a research-backed model that weighs creation, modification, and knowledge decay rather than raw commit counts.
Read the bus factor guide →Technical due diligence is the process of evaluating a software company's code, infrastructure, intellectual property, and engineering team before an acquisition or investment. Beyond code audits, modern technical due diligence quantifies the human risk: who understands the systems, how concentrated that knowledge is, and whether those engineers will stay through integration.
Read the due diligence guide →Key person dependency (also called key man risk) describes the organizational exposure that exists when business-critical knowledge concentrates in one or a few individuals. In software engineering, key person dependency typically appears as single-author files, one-reviewer modules, and incident response that always routes to the same engineer.
Read the key person risk guide →Degree of Authorship is a normalized score (0 to 1) that measures how strongly an engineer owns a given file. Introduced by Fritz et al., DOA considers first authorship (who created the file), deliveries (how often they modify it), and acceptances (how much the file has changed since their last edit). Engineers above 0.75 are treated as authoritative subject matter experts.
Read the DOA explainer →Learn more about how ContributorIQ analyzes your engineering organization.
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.
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.
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.
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.
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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