Features
Method-level runtime traces with arguments, return values, SQL, and timing
Diff execution traces before vs. after code changes to detect behavior shifts
Auto-generate deterministic JUnit 5 replay tests from captured traces
MCP (Model Context Protocol) server for AI agent runtime context
Integrate with Testcontainers for replaying external API interactions
Instrument HTTP clients (RestTemplate, OpenFeign), JDBC, Kafka, and more
Support Spring Boot full-context integration tests with auto-stubbed boundaries
Generate one-click Postman collections from runtime traces
Run autonomous regression suites in CI/CD without token usage
Self-hosted Docker deployment for air-gapped environments
WebSocket, SOAP, and WebSocket tracing
PR review with runtime comparison (baseline main + PR diff)
Automatic PII masking before capture
Binary capture and compression for low overhead (0.5-5% CPU)
Local-first privacy (data stays in your infrastructure)
Live knowledge graph from code, commits, issues, and docs
Feasibility analysis: flags buildable vs risky items
Technical design document generation grounded in service topology
Impact assessment maps services, APIs, and dependencies across repos
Auto-scoping epics into Jira/Linear stories with effort estimates
One-shot production code generation grounded in service patterns
AI code reviews with cross-repo impact analysis
Production issue triage via MCP
Conversational learning from Slack and Jira
Accelerated onboarding via system-level Q&A in coding agents
Create Jira tickets and merge requests from Slack
MCP server for integration with Cursor, Claude Code, Codex
On-prem or cloud deployment
No code storage or model training
