Chonkie Labs is Context as a Service, built on Chonkie OSS. Upload your documents and get instant access to semantic search, AI chat, deep research, and MCP deployments. No OCR to configure, embeddings to manage, vector DBs to maintain, or chunking to debug. Just context, served fresh.
Key Features
Knowledge Bases
Upload and organize documents into knowledge bases with automatic chunking,
embedding, and indexing. Supports PDFs, Word docs, markdown, text files, and
more.
Semantic Search
Perform accurate semantic search across your documents with three modes:
Fast for quick queries, Balanced for the best mix of speed and relevance,
and Deep for comprehensive analysis.
Document Chat
Chat with your data through our web UI or OpenAI-compatible APIs. Chonkie
automatically retrieves context from your knowledge bases for accurate,
grounded responses.
Research Agents
Build research agents in natural language. Chonkie pulls context from your
knowledge bases automatically. Generate detailed reports with citations in
minutes.
MCP Integration
Expose your knowledge bases as Model Context Protocol (MCP) servers. Connect
them to Cursor, Claude, and other MCP-compatible tools for seamless AI
integration.
API Native
Everything in Labs is accessible via RESTful APIs and OpenAI-compatible
endpoints. From chunking a single document to building a full agent.
Why Use Chonkie Labs?
Building a production-ready retrieval system from scratch means dealing with:- Infrastructure complexity: OCR, vector databases, embeddings services, storage buckets, API servers
- Chunking challenges: Choosing the right strategy, optimizing chunk sizes, handling edge cases
- Integration headaches: Connecting embeddings, rerankers, LLMs, and vector stores
- Maintenance burden: Monitoring, scaling, updating dependencies, handling failures
Instant Setup
Create a knowledge base and start searching in minutes, not weeks. No
infrastructure to provision or configure.
Battle-Tested Chunking
Powered by Chonkie’s proven chunking algorithms, refined through thousands
of real-world use cases.
Managed Infrastructure
We handle OCR, vector databases, storage, embeddings, and API hosting. You
focus on your application.
API-First Design
RESTful APIs and OpenAI-compatible endpoints make integration painless.
Works with your existing tools.
Use Cases
Document Q&A
Document Q&A
Build intelligent document search and question-answering systems. Perfect
for customer support, internal wikis, and research databases.
AI Assistants
AI Assistants
Deploy domain-specific AI assistants that pull context from your
documentation. Create expert agents for sales, support, or engineering.
Research Tools
Research Tools
Power research applications with deep semantic search. Surface relevant
information from large document collections instantly.
Contextual AI Coding
Contextual AI Coding
Connect your knowledge bases to IDEs via MCP. Give developers instant access
to documentation and internal resources.