Generative AI

Ragforge - RAG-as-a-Service Platform

A multi-tenant RAG-as-a-Service platform that turns any document collection into a queryable API in minutes - three REST endpoints, scoped API keys, and a self-serve console. No vector infrastructure to manage.

Remote2025

Key Outcome

3-endpoint RAG integration

Full retrieval-augmented generation shipped from a single API key - no vector infrastructure required.

The Problem

Teams that want retrieval-augmented generation spend weeks building and babysitting their own vector database, chunking pipeline, and embedding logic before shipping anything useful.

Our Solution

Built Ragforge as a fully managed RAG platform. Users create scoped projects, each with its own Pinecone namespace and API key. The entire integration surface is three endpoints - ingest, query, and delete - backed by a LangGraph retrieval pipeline and a self-serve web console.

Key Features

Multi-tenant project isolation - separate RAG namespace per team or client

Scoped API keys per project - rotate or revoke without affecting others

Three-endpoint integration surface: ingest, query, delete

Automated chunking, embedding, and Pinecone indexing on upload

LangGraph-powered retrieval and generation pipeline

Per-project usage dashboard: documents ingested, queries served, active keys

Built-in developer docs with copy-paste request examples

Organization-level account management and project grouping

Technology Stack

PythonPineconeLangGraphFastAPIReactTypeScriptRAGVector DB

Project Visuals

Ragforge - RAG-as-a-Service Platform screenshot 1
Ragforge - RAG-as-a-Service Platform screenshot 2
Ragforge - RAG-as-a-Service Platform screenshot 3
Ragforge - RAG-as-a-Service Platform screenshot 4

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