Complete visibility and control over Claude Code workflows with comprehensive auditability, token-level cost tracking, and compliance-ready reporting. Self-hosted for maximum data sovereignty.
Enterprise-ready • Data sovereignty • Production-grade observability
Real-time conversation tracking with comprehensive analytics and intuitive interface
Complete observability, cost management, and compliance controls for AI-assisted development at scale
Comprehensive logging of every AI interaction with full conversation history, model versions, and tool executions. Meets compliance requirements for regulated industries with immutable records.
Token-level cost tracking with detailed breakdowns of input, output, and cache usage. Identify optimization opportunities and allocate AI spend across projects and teams with precision.
Full visibility into all AI tool operations with parameters, results, and error states. Understand exactly what code changes were made, when, and by which AI model for complete operational transparency.
Complete data sovereignty with on-premise deployment. Your AI conversation data never leaves your infrastructure, ensuring compliance with data residency and privacy regulations.
Comprehensive dashboards tracking AI usage patterns, model performance metrics, and team productivity indicators. Export compliance-ready reports for stakeholder communication and budget justification.
Transform AI interactions into organizational knowledge. Full-text search enables teams to leverage past solutions, reduce duplicate effort, and maintain institutional knowledge across development cycles.
Real-time metrics, conversation insights, and cost analytics in a modern, intuitive interface
Monitor token usage, conversation metrics, and cost analytics with interactive charts and visualizations
Browse conversations by project with powerful search and filtering capabilities
Rapid deployment with containerized infrastructure and zero-config data pipeline integration
Deploy the containerized stack: git clone https://github.com/davidgaribay-dev/rewind.git
Compatible with Docker, Kubernetes, or bare-metal deployments.
Configure data source paths via environment variables or web-based settings interface. Supports centralized configuration management for multi-environment deployments.
Execute docker-compose up -d for fully automated
deployment. Infrastructure as code handles database migrations, service dependencies, and health checks.
Initiate ETL processes through web UI or CLI with real-time progress monitoring. Supports incremental updates and scheduled batch processing for large-scale operations.
Access comprehensive analytics, audit logs, and compliance reports through the web interface. RESTful API available for integration with existing enterprise monitoring and BI tools.
Address critical AI governance challenges with comprehensive solutions designed for enterprise scale
Built-in audit logging, immutable conversation records, and data retention controls ensure readiness for SOC 2, ISO 27001, GDPR, and industry-specific regulations.
Self-hosted deployment ensures sensitive AI conversations never leave your infrastructure. Complete control over data location, access controls, and encryption at rest and in transit.
Token-level granularity enables precise cost allocation, budget forecasting, and spend optimization. Identify inefficient patterns and justify AI investments with quantifiable metrics.
Real-time dashboards and historical analytics provide actionable insights into AI adoption, team productivity, model performance, and development velocity trends.
Battle-tested technologies with proven scalability, security, and maintainability for mission-critical AI operations
From startups to enterprises, organizations rely on Rewind for AI governance, compliance, and operational excellence
Real-time AI spend tracking with per-project allocation, budget alerts, and ROI analysis for cost center accountability
Complete audit trails for SOC 2, ISO 27001, and industry regulations with immutable conversation logs and model version tracking
Review AI-generated code changes with full context, ensuring code quality standards and reducing technical debt from AI workflows
Measure AI adoption rates, identify power users, and optimize team productivity through data-driven insights
Trace production issues back to specific AI interactions, enabling faster incident resolution and preventing recurrence
Preserve institutional knowledge through searchable AI conversation archives, reducing onboarding time and decision-making uncertainty
Open source, self-hosted platform designed for organizations that require complete data sovereignty, comprehensive auditability, and production-grade AI operations management
# Clone and configure
git clone https://github.com/davidgaribay-dev/rewind.git
cd rewind
cp .env.example .env
# Set your Claude Code data path in .env (defaults to ~/.claude/projects)
# REWIND_DATA_PATH=~/.claude/projects
# Start everything (one command!)
docker-compose up -d
# That's it! 🎉
# Web: http://localhost:8430
# API: http://localhost:8429