What is Graphlit?
Building AI-powered applications often involves wrangling unstructured data, integrating multiple tools, and managing complex infrastructure. Graphlit simplifies this process by offering a serverless RAG-as-a-Service platform that handles everything from data ingestion to intelligent text extraction, vector embeddings, and conversation history. Whether you're building chatbots, summarizing documents, or creating knowledge graphs, Graphlit provides the tools you need—without requiring you to manage servers or stitch together disparate systems.
Key Features
✨ Ingest Data from Any Source
Connect to web pages, cloud storage (Google Drive, Dropbox), collaboration tools (Slack, Notion), project management platforms (Jira), email, RSS feeds, and more.
Benefit: Focus on building your app while Graphlit pulls in data from wherever it lives.
✨ Automated Text Extraction and Chunking
Extract structured text from PDFs, Word documents, images, audio, and video using OCR and advanced LLMs.
Benefit: Save time by automating the tedious task of preparing unstructured data for AI models.
✨ Built-In Vector Search and Embeddings
Perform semantic searches across your content with metadata filtering and similarity-based queries.
Benefit: Retrieve relevant information faster, even when dealing with massive datasets.
✨ Multimodal Support
Process not just text but also images, audio, and video with integrations like OpenAI GPT-4o and Anthropic Sonnet 3.5.
Benefit: Build richer, multimodal AI applications without worrying about compatibility issues.
✨ Usage-Based Pricing
Pay only for what you use, starting at $0.10 per credit. Free tier includes 100 credits to get started.
Benefit: Scale your projects affordably, whether you're an individual developer or part of a large team.
Use Cases
1. Building a Chatbot for Customer Support
Imagine creating a chatbot that answers customer questions based on internal documentation, FAQs, and past support tickets. With Graphlit, you can ingest all these resources, generate vector embeddings, and enable semantic search to ensure accurate responses. No need to set up databases or manage infrastructure—just focus on designing the conversational flow.
2. Summarizing Research Papers for Academics
As a researcher, you might want to quickly summarize dozens of academic papers stored in PDF format. Graphlit extracts text, chunks it intelligently, and uses LLMs to generate concise summaries. You can even enrich the summaries with external API data, such as related Wikipedia articles.
3. Creating Knowledge Graphs for Enterprises
For businesses looking to organize their intellectual property, Graphlit automatically builds knowledge graphs from ingested content. Enable entity extraction to identify key concepts (people, places, products) and enrich them with metadata from sources like Crunchbase or Wikipedia. This creates a dynamic, interconnected view of your organization's data.
Conclusion
Graphlit empowers developers to build sophisticated AI applications without the hassle of managing infrastructure or integrating countless tools. Its comprehensive feature set—from automated ETL pipelines to multimodal support—makes it ideal for anyone working with unstructured data. Whether you're prototyping a chatbot, analyzing research papers, or organizing enterprise knowledge, Graphlit accelerates development and reduces complexity.
More information on Graphlit
Top 5 Countries
46.94%
32.25%
10.54%
5.48%
4.79%
United States
India
United Kingdom
Japan
Canada
Traffic Sources
48.08%
32.98%
10.31%
7.36%
1.19%
0.06%
Direct
Search
Social
Referrals
Paid Referrals
Mail
Graphlit was manually vetted by our editorial team and was first featured on 2023-12-25.
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Text Analytics
Semantic Search
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Text Summarization
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