Multi-source ingestion
Ingests files, text, URLs, feeds, and connected accounts, including PDFs, audio, video, web pages, Slack messages, email, and knowledge base sources.
Overview
Graphlit is a context layer for AI agents and applications that need to work with organizational knowledge instead of isolated chat memory. It combines ingestion, extraction, search, chat, and knowledge graph workflows behind a single API.
The product is designed to bring content from files, web pages, messages, storage systems, and business tools into a searchable context layer. The site emphasizes real-time or continuous sync, provenance, and grounded answers so agents can use source-backed information rather than static prompts or ad hoc glue code.
Core capabilities
Workflow-based processing
Supports preparation, extraction, and enrichment workflows, with built-in transcription, OCR, embeddings, and completions.
Search and chat with grounding
Provides semantic search, keyword search, and hybrid search, plus source-grounded conversations with citations for retrieval-augmented use cases.
Knowledge graph modeling
Extracts entities, observables, relationships, and temporal state to build organizational knowledge graphs rather than simple document indexes.
Connector ecosystem
Connects to tools such as Slack, GitHub, Jira, Notion, Google Drive, S3, Gmail, Dropbox, and more, with continuous sync mentioned in the product messaging.
Developer access
Offers SDKs and an MCP server for developer workflows, including TypeScript, Python, and .NET support and access from tools such as Claude, Cursor, and ChatGPT on higher plans.
Common use cases
Grounded AI chat
Build assistants that answer from company knowledge with source citations, multi-turn memory, and retrieval over documents, messages, and connected apps.
Unified knowledge search
Sync and search operational content from tools like Slack, GitHub, Jira, Notion, and email so teams can find context without manual ETL.
Knowledge graph workflows
Extract people, companies, relationships, events, and ownership from content to support graph queries and relationship-aware applications.
Document and media processing
Process PDFs, web pages, audio, video, and office files through ingestion, transcription, OCR, and enrichment pipelines for downstream AI use.
Agent context infrastructure
Connect external data sources to AI agents through MCP and SDKs so apps can retrieve context and trigger actions from familiar developer tools.
Pros and Cons
Pros
- Combines ingestion, extraction, search, chat, and knowledge graphs in one platform.
- Supports a wide range of content types and connected sources, including files, messages, feeds, and business apps.
- Includes grounded retrieval features such as citations and source traceability.
- Offers usage-based pricing with a free tier and no credit card required to start.
- Provides SDKs and an MCP server for developer workflows.
Cons
- The site does not show every integration detail on the main pages, so buyers may need to check the docs for source-specific behavior.
- Some enterprise-oriented items on the pricing page are marked as coming soon, including SLA and SOC 2 on the Growth plan.
- The public pages emphasize platform capabilities more than implementation constraints, so setup effort is not fully transparent from the marketing pages alone.
FAQ
What is Graphlit used for?
Graphlit is used to ingest content, extract structure, and make it searchable for AI applications that need grounded context. The site positions it as a context layer for AI agents, with support for search, RAG, chat, and knowledge graphs.
Does Graphlit offer a free plan?
The pricing page shows a Free tier with limited usage and paid plans for Hobby, Starter, and Growth, plus a Custom option for larger integration and agent work. The site also says there is a free project to get started and that no credit card is required for the free tier.
Which SDKs does Graphlit support?
Yes. The site references SDKs for TypeScript, Python, and .NET, and the home page shows example code in TypeScript.
What kinds of integrations does Graphlit support?
Graphlit’s integrations page describes ingestion, preparation, and delivery across connected tools. The site highlights sources such as Slack, GitHub, Jira, Notion, Gmail, Google Drive, S3, Dropbox, and similar systems.
What capabilities are included in the platform?
The pricing page says Graphlit includes ingestion and extraction, search and RAG, knowledge graphs, and agent context in one platform price. It also calls out citations, configurable workflows, and content feeds.
Quick Facts
- Category
- AI context layer / developer platform
- Primary users
- AI product teams, developers, and teams building agents or knowledge workflows
- Source domain
- graphlit.com
- Core workflow
- Ingest content, extract structure, search it, and use it as grounded context for agents
- Pricing model
- Free tier plus usage-based paid plans
- Supported access
- Web app, API, SDKs, and MCP server
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