stache.tech

What it is

Stache is an enterprise-grade RAG knowledge retrieval platform for AI applications, designed to make an organization’s internal knowledge instantly accessible to AI apps. It covers document ingestion, automatic chunking, embeddings, semantic search, retrieval augmentation, and answer synthesis, with an emphasis on enterprise security and developer experience. Its current positioning is closer to deployable RAG infrastructure for AWS than a pure SaaS knowledge base product.

Core capabilities

On the AI side, Stache uses Cohere embeddings via AWS Bedrock for semantic retrieval and can call Claude for answer synthesis, making it suitable for turning enterprise documents into a question-answerable knowledge base. Document ingestion supports PDF, DOCX, PPTX, EPUB, and plain text, and includes OCR, automatic chunking, and metadata extraction. Its integrations are fairly complete, with a CLI, REST API, Python SDK, and MCP Server, and it can connect to Claude Desktop and Claude Code. A namespace mechanism allows knowledge to be isolated by team, project, or document type.

Pricing and deployment

The page clearly states that Self-Hosted is Free & Open Source, deployable to your own AWS account via SAM/CloudFormation, with an emphasis on full control and no vendor lock-in. Managed Cloud is still listed as Coming Soon. Enterprise offers custom deployment, SLAs, dedicated support, and professional services, but requires contacting sales; specific pricing and free quotas are not disclosed.

Pros and cons

Its strengths include being open source and self-hosted, keeping data inside the customer’s AWS account, support for MCP and Claude, a relatively broad range of ingestion formats, plus access control, audit logs, and a middleware-based extensibility approach. The limitations are also clear: it is heavily tied to the AWS ecosystem, including AWS Bedrock, S3 Vectors, and DynamoDB; SOC 2 is only marked as Ready; the managed cloud version is not yet available; and details around Chinese-language support, retrieval evaluation, citation/source tracing, and hallucination control are not explained.

Who it is for and access from China

Stache is better suited to AI engineering teams, internal knowledge base teams, and developers who already have AWS expertise and need to build their own enterprise RAG backend or connect Claude to private knowledge. For non-technical teams or users looking for an out-of-the-box SaaS product, the barrier to entry is relatively high. The text does not specify access conditions from China. Because it depends on external services such as AWS Bedrock, Claude, and GitHub, real-world deployment may be affected by network access, account availability, and payment requirements. Alternatives include Dify, LangChain, LlamaIndex, AnythingLLM, and Flowise.