Graphlit

Serverless RAG-as-a-Service for building AI apps and agents on unstructured data.

4.7 (6)

נבדק על ידי Daniel Nikulshyn·עודכן מאי 2026

Knowledge Graph Serverless RAG Backend-as-a-Service Vector Search API Developer Tools

סקירה

Graphlit is a managed backend platform that handles the heavy lifting of retrieval-augmented generation, letting developers ingest, process, and query unstructured content without assembling their own pipeline. It connects to sources like documents, audio, video, and web data, then automatically extracts text, generates embeddings, and stores everything in a knowledge graph ready for LLM queries. The platform exposes its capabilities through APIs and SDKs, making it suitable for teams building AI agents, chatbots, search experiences, or content workflows. By abstracting vector storage, parsing, transcription, and orchestration into a single service, Graphlit aims to shorten the path from raw data to production-ready AI features.

תכונות עיקריות

Automated ingestion of documents, media, and web sources
Built-in embeddings and vector search
Knowledge graph construction from unstructured data
Transcription and content extraction
Agent and workflow orchestration tools
REST API and developer SDKs

מקרי שימוש

Build AI chatbots over internal documents

Ingest company documents and let Graphlit handle parsing, embeddings, and retrieval so developers can quickly build chatbots that answer questions grounded in proprietary content.

Power AI agents with multimodal context

Use Graphlit's APIs and SDKs to give agents searchable access to audio, video, and web sources through a unified knowledge graph without building custom ingestion pipelines.

Add semantic search to applications

Leverage built-in embeddings and vector search to deliver semantic search experiences across mixed content types, skipping the work of managing vector databases directly.

Automate media transcription and analysis workflows

Feed audio and video into Graphlit to automatically transcribe, extract text, and orchestrate downstream LLM workflows for content processing or summarization.

יתרונות וחסרונות

יתרונות

Eliminates the need to build a custom RAG stack
Handles diverse content types including audio and video
Serverless model reduces infrastructure overhead
SDKs and APIs simplify integration

חסרונות

Less control than a self-hosted pipeline
Usage-based pricing can be unpredictable at scale
Requires trusting a third party with your data

ביקורות

4.7

ממוצע מ-6 דירוגים.

התחבר כדי להשאיר ביקורת.

Omar Haddad

Compared a few options

Evaluated this against two competitors. Where it wins: knowledge graph construction from unstructured data and eliminates the need to build a custom RAG stack. Where it lags: usage-based pricing can be unpredictable at scale. On balance the feature set — especially built-in embeddings and vector search — justifies the 4 stars for our use case.

Aisha Khan

Skeptical, then convinced

I went in skeptical — most tools in this space overpromise. It actually delivers on transcription and content extraction, and sDKs and APIs simplify integration caught me off guard. Usage-based pricing can be unpredictable at scale is why this isn't a perfect score, still, I'd recommend giving it a real trial.

Camille Laurent

Compared a few options

Evaluated this against two competitors. Where it wins: automated ingestion of documents, media, and web sources and serverless model reduces infrastructure overhead. On balance the feature set — especially built-in embeddings and vector search — justifies the 5 stars for our use case.

Robert Ainsworth

Use it every day

Honestly didn't expect to like it this much. REST API and developer SDKs is exactly what I needed, and sDKs and APIs simplify integration. but I reach for it almost every day now and it just clicks.

Priya Nair

Use it every day

Honestly didn't expect to like it this much. REST API and developer SDKs is exactly what I needed, and eliminates the need to build a custom RAG stack. but I reach for it almost every day now and it just clicks.

Frank Müller

Use it every day

Honestly didn't expect to like it this much. REST API and developer SDKs is exactly what I needed, and sDKs and APIs simplify integration. I do wish less control than a self-hosted pipeline, but I reach for it almost every day now and it just clicks.