opensearch-ai Alternatives

Same rag framework intent with agent_memory, rag overlap.

Fit: Strong replacement candidate with overlapping indexed use cases.

The Memory Layer for AI Agents - Drop-in memory infrastructure for AI agents and apps. Context that persists. Built for production.

Same rag framework intent with agent_memory, rag overlap.

Fit: Strong replacement candidate with overlapping indexed use cases.

A filesystem designed for agents, with SOTA retrieval, automatic memory profiles, sync engine. Drop any file type (pdf, images, videos), and grep through them.

Same rag framework intent with agent_memory, rag overlap.

Fit: Strong replacement candidate with overlapping indexed use cases.

Research project. A Memory solution for users, teams, and applications.

Same rag framework intent with rag overlap.

Fit: Strong replacement candidate with overlapping indexed use cases.

Sim is the collaborative workspace to build, deploy, and monitor AI agents and workflows. Used by 100,000+ builders.

Same rag framework intent with agent_memory, rag overlap.

Fit: Strong replacement candidate with overlapping indexed use cases.

VeritasGraph — open-source Knowledge Graph & GraphRAG framework on GitHub. Build multi-hop reasoning, ontology-aware retrieval, and verifiable attribution over your own data. Nodes, edges, RDF, linked-data — runs locally or in the cloud.

Same rag framework intent with rag overlap.

Fit: Strong replacement candidate with overlapping indexed use cases.

AI chat for any model.

Same rag framework intent with agent_memory, rag overlap.

Fit: Strong replacement candidate with overlapping indexed use cases.

Supermemory plugin for OpenCode

Same rag framework intent with rag overlap.

Fit: Strong replacement candidate with overlapping indexed use cases.

Build Real-Time Knowledge Graphs for AI Agents

Same rag framework intent with rag overlap.

Fit: Strong replacement candidate with overlapping indexed use cases.

TensorRT LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and supports state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs. TensorRT LLM also contains components to create Python and C++ runtimes that orchestrate the inference execution in a performant way.

Same rag framework intent with agent_memory, rag overlap.

Fit: Strong replacement candidate with overlapping indexed use cases.

What are the principles we can use to build LLM-powered software that is actually good enough to put in the hands of production customers?

Same rag framework intent with rag overlap.

Fit: Strong replacement candidate with overlapping indexed use cases.

Easiest and laziest way for building multi-agent LLMs applications.

Same rag framework intent with agent_memory, rag overlap.

Fit: Strong replacement candidate with overlapping indexed use cases.

The explainable, local-first memory engine for AI agents. One ~9 MB binary fuses vector + graph + columnar under VelesQL; why() returns the evidence path behind every recall. No cloud, no glue code — runs on server, browser, mobile and desktop.