Graphlit
AI platform for unstructured data
How it performs on Versalist
Real signals from Versalist challenges, evaluations, and community usage.
Be the first to run a challenge with this tool and create a useful signal for the next builder.
Challenges using Graphlit
Prompts for Graphlit
About Graphlit
What this tool does and where it fits best.
Platform for building AI applications on unstructured data, offering APIs for ingestion, enrichment, and querying.
What Graphlit is good at
The use cases this tool handles best.
Unstructured Data Ingestion
Automated ETL pipeline that ingests any unstructured data format including documents, HTML, Markdown, audio, video, images, emails, and code files. Supports data connectors for Google Drive, Notion, GitHub, Slack, OneDrive, and cloud storage (S3, Azure Blob).
Conversational Knowledge Graph
Automatically extracts knowledge graph entities and relationships between people, organizations, places and topics found in content. Builds a searchable, conversational knowledge graph using AI that can be queried through natural language.
RAG-as-a-Service Platform
Serverless Retrieval-Augmented Generation platform that provides managed vector databases, graph databases, and integrations with leading LLMs (OpenAI, Azure OpenAI, Anthropic, Mistral). Eliminates need for Langchain, Pinecone, or S3 setup.
Multimodal Content Processing
Processes multiple content types with built-in capabilities including audio transcription for podcasts and videos, OCR for images and PDFs, web scraping for websites, and Markdown extraction. Automatically indexes and makes content searchable.