Ragie

Managed RAG-as-a-service with built-in hallucination control.

Vectara is an enterprise GenAI platform that delivers retrieval-augmented generation as a managed service, bundling ingestion, embedding, retrieval, reranking, and grounded generation behind one API. It ships first-party retrieval and generation models and a built-in hallucination-evaluation model (HHEM) to measure and reduce ungrounded answers. It targets regulated, accuracy-critical applications and AI agents.

One API for AI agent memory: ingest, extract, store, retrieve.

A cloud-native platform that gives AI agents semantic memory and operational context through a single API. It ingests documents, audio, video, and web pages, extracts entities and relationships, and handles storage and retrieval so you don't assemble the RAG pipeline yourself. Integrates with frontier models from OpenAI, Anthropic, and Google for extraction.

The data framework for LLM apps — RAG, agents, and document workflows.

An open-source framework (Python + TypeScript) for connecting LLMs to your data — ingestion, indexing, retrieval, and agentic document workflows. Pairs with the managed LlamaCloud (LlamaParse) for production parsing and extraction. The most-used RAG framework after LangChain.

Source-available platform for building AI agents for support and docs.

Inkeep is an AI agent platform for customer-experience and operations teams, pairing a no-code visual builder with a TypeScript framework that stay in two-way sync. Agents draw on unified search and RAG over your docs and company data, connect to apps via MCPs and integrations, and report monitoring insights. The Inkeep Agents framework is source-available on GitHub and self-hostable, alongside a managed cloud.