Audit any GitHub repository with Deterministic AI
Audit → Diagnose → Fix → Test → Verify. The platform understands repository architecture, hidden bug propagation paths, predictive risk, and autonomous remediation loops with evidence-backed guardrails.
Try Instant Sample Repositories
Click any pre-configured repository to run an instant benchmark audit
vulnerable-python-app
Intentionally vulnerable Flask web application with leaked AWS keys, SQL injection (CWE-89), command injection, bare excepts, and CVE-compromised dependencies.
clean-modular-ts
Production-grade modular TypeScript microservice with 100% unit tests, Zod validation, GitHub Actions CI, and clean architecture.
fastapi
High-performance, easy to learn, fast to code Python web framework for APIs based on standard Python type hints.
shadcn-ui
Beautifully designed, accessible components built with Radix UI and Tailwind CSS. The gold standard for modern React frontend architecture.
express
Fast, unopinionated, minimalist web framework for Node.js powering millions of backend microservices worldwide.
microservices-go-backend
Distributed event-driven Go microservices architecture with gRPC, Redis Pub/Sub, and PostgreSQL order state management.
ml-predictive-pipeline
End-to-end PyTorch deep learning training and inference pipeline with data preprocessing, scaling, and feature engineering.
missing-docs-deps
Legacy Python backend with zero automated tests, missing README documentation, and outdated dependencies.
One architecture for 1 repo or 1 million repos
The platform is designed around queue-driven workers, shared analyzers, pluggable execution, and cached results so the system scales by adding workers—not by rewriting the architecture.
Queue-based parallel analysis
Repos enter a durable task queue and independent workers fan out analysis across files, modules, dependencies, and security signals in parallel.
Pluggable analyzer mesh
Security, architecture, bug detection, performance, quality, and AI evaluation become independently swappable modules behind the same orchestration contract.
Incremental audits
Analyze only changed files, AST paths, or dependency deltas to reduce compute and keep repeated scans fast and deterministic.
Horizontal worker scale
The same job contract works for a single repo and a fleet of millions—only queue concurrency, caching, and worker count change.
Default production stack
Users, repos, audits, findings, scoring history, permissions, snapshots metadata, and job ownership.
Queue orchestration, rate limits, deduplication, short-lived job state, and distributed locking.
Repository snapshots, logs, raw analyzer output, large reports, and export bundles.
Code embeddings, semantic search, architectural similarity, and “find similar risky patterns” queries.
Optional large-scale tier
Add ClickHouse only when audit/event volume requires very large-scale analytics, historical trends, and real-time dashboards across millions of audits.
- • Cached AST and semantic embeddings to avoid repeat work
- • Async GitHub webhooks for automatic repos and PR audits
- • Sandboxed execution for untrusted repositories
- • Centralized historical risk trends and repository health snapshots
Deterministic Static AST
Never hallucinates file issues. Inspects real AST complexity, bare excepts, wildcard imports, and nesting depth with line-by-line evidence.
Interactive Agent Tool-Calling
Equipped with 8 runtime tools. Ask why files are difficult to maintain and watch the agent inspect churn, read functions, and run live AST metrics.
Actionable GitHub Automation
Generates copy-paste GitHub issue markdown, proposed PR unified diff patches, and publishes directly via GitHub REST API with one click.