# Arcbeam Documentation

## Docs

- [Review Traces Together](https://docs.arcbeam.ai/v0/collaboration/review-traces-together.md): Collaborative workflows for team-based trace evaluation
- [Context Management](https://docs.arcbeam.ai/v0/core-concepts/context-management.md): Managing what your AI remembers in conversations
- [Cost Optimization](https://docs.arcbeam.ai/v0/core-concepts/cost-optimization.md): Reducing AI costs without sacrificing quality
- [Data Lineage](https://docs.arcbeam.ai/v0/core-concepts/data-lineage.md): Trace AI outputs back to source documents
- [Data Processing](https://docs.arcbeam.ai/v0/core-concepts/data-processing.md): How to prepare your information for AI
- [Data Sources](https://docs.arcbeam.ai/v0/core-concepts/datasets-and-data-sources.md): Where your AI gets its knowledge from
- [Evaluations](https://docs.arcbeam.ai/v0/core-concepts/evaluations.md): Measuring and improving your AI's quality
- [Model Selection](https://docs.arcbeam.ai/v0/core-concepts/model-selection.md): Choosing the right AI model for your needs
- [Observability](https://docs.arcbeam.ai/v0/core-concepts/observability.md): Understanding what your AI is actually doing
- [Dataset Analytics](https://docs.arcbeam.ai/v0/data-insights/dataset-analytics.md): Understand usage patterns and quality across your entire datasets
- [Document Usage Analytics (Coming Soon)](https://docs.arcbeam.ai/v0/data-insights/see-what-data-is-used.md): Track how individual documents are used across all traces
- [Data Lineage](https://docs.arcbeam.ai/v0/data-insights/track-data-changes.md): Track which original source files power your AI responses
- [Find Problematic Traces](https://docs.arcbeam.ai/v0/debugging/find-problematic-traces.md): Navigate, filter, and explore traces to identify issues
- [Retrieved Documents](https://docs.arcbeam.ai/v0/debugging/trace-issues-to-source-data.md): See which documents from your knowledge base influenced each LLM response
- [Understand Retrieval Quality](https://docs.arcbeam.ai/v0/debugging/understand-retrieval-quality.md): Analyze and improve document retrieval effectiveness
- [Organizing Data by Environment](https://docs.arcbeam.ai/v0/deployment/environments.md): Tag and filter traces by environment (dev, staging, production)
- [Installation (Self Hosted)](https://docs.arcbeam.ai/v0/deployment/self-host.md): Complete installation guide for deploying Arcbeam
- [Troubleshooting](https://docs.arcbeam.ai/v0/deployment/troubleshooting.md): Fix common issues when sending traces to Arcbeam
- [LangChain Integration](https://docs.arcbeam.ai/v0/integrations/ai-frameworks/langchain.md): Send traces from LangChain applications to Arcbeam
- [LangGraph Integration](https://docs.arcbeam.ai/v0/integrations/ai-frameworks/langgraph.md): Send traces from LangGraph applications to Arcbeam
- [PGvector Integration](https://docs.arcbeam.ai/v0/integrations/vector-databases/pgvector.md): Connect PostgreSQL with PGvector to Arcbeam for data lineage tracking
- [Introduction ](https://docs.arcbeam.ai/v0/introduction.md): Observability and monitoring platform for AI applications with full trace visibility and data lineage tracking
- [Quickstart](https://docs.arcbeam.ai/v0/quickstart.md): Get Arcbeam running and send your first trace in 5 minutes
- [Glossary](https://docs.arcbeam.ai/v0/resources/glossary.md): Key terms and definitions for LLM observability and Arcbeam
- [Support](https://docs.arcbeam.ai/v0/resources/support.md): Get help with Arcbeam and contact our team
- [Connect Your Data Sources](https://docs.arcbeam.ai/v0/setup/add-data-sources.md): Connect your vector databases to Arcbeam to see which documents influenced each trace
- [Log Your Traces](https://docs.arcbeam.ai/v0/setup/connect-your-ai-system.md): Learn how Arcbeam captures traces from your LLM applications
- [Setting Up Projects](https://docs.arcbeam.ai/v0/setup/organize-with-projects.md): Organize and monitor your LLM applications with Arcbeam projects

## Optional

- [GitHub](https://github.com/arcbeam)
- [Support](mailto:support@arcbeam.ai)