Khoj

NotebookLM

AI-powered research assistant

NotebookLM is Google's AI-powered research and note-taking tool that lets you upload your own documents and interact with them using natural language. It helps summarize sources, generate insights, and answer questions based on your uploaded content.

Mem0

The universal persistent memory layer for AI agents & LLM apps

Mem0 (formerly Embedchain) is a universal, persistent memory architecture designed to solve the critical context amnesia problem in modern AI applications. While foundational LLMs forget user preferences and past interactions the moment a session ends, Mem0 maintains a continuous, self-improving memory graph across user sessions, agents, and applications. With Mem0, developers can build personalized AI assistants, customer support agents, and autonomous workflow bots that remember user preferences, past project decisions, and communication styles over months and years. Mem0 operates as both an open-source self-hostable Python/TypeScript library and a managed cloud platform, providing sub-100ms vector search, episodic memory extraction, and automated memory consolidation without manual prompt engineering.

RunPod

Globally distributed GPU cloud and serverless platform for AI inference and training

RunPod is a leading globally distributed GPU cloud and serverless computing platform engineered specifically for artificial intelligence workloads. It provides developers, AI researchers, and enterprises with on-demand access to top-tier NVIDIA GPUs (including H100, A100, L40S, and RTX 4090) at up to 80% lower cost than traditional legacy hyperscalers.

Qdrant

High-performance vector database and similarity search engine for AI

Qdrant is an open-source, high-performance vector database and similarity search engine engineered in Rust for production AI systems, semantic search engines, and Retrieval-Augmented Generation (RAG) pipelines. It provides lightning-fast nearest-neighbor search with rich payload filtering and custom distance metrics. Unlike traditional databases adapted for vectors, Qdrant was designed from day one to handle high-dimensional neural embeddings at scale. Its Rust engine provides memory-efficient vector quantization (scalar, product, and binary), allowing engineering teams to search billions of vectors on cost-effective cloud hardware.

LlamaIndex

Leading data framework for connecting custom data sources to LLMs and Agentic RAG workflows.

LlamaIndex is the premier open-source data framework designed to bridge private, enterprise, and unstructured data with large language models. By providing sophisticated data connectors, automated parser modules, semantic chunking algorithms, and multi-document index structures, LlamaIndex enables developers to build context-augmented LLM applications and autonomous knowledge retrieval engines with minimal boilerplate. From parsing complex multi-page PDF documents and financial spreadsheets to orchestrating complex Agentic RAG workflows that query multiple disparate databases, LlamaIndex handles the complete data ingestion, indexing, and query evaluation lifecycle.

Stanford STORM

Autonomous deep research system synthesizing multi-perspective, citation-backed Wikipedia-style reports

Stanford STORM (Synthesis of Topic Outlines through Retrieval and Multi-perspective Question Asking) is an open-source AI research system developed by Stanford University. It autonomously conducts deep web investigations, generates diverse stakeholder interview perspectives, and synthesizes exhaustive, citation-backed long-form reports. Unlike standard search engines that produce single-paragraph summaries, STORM simulates a collaborative expert panel to research complex topics thoroughly and assemble referenced research dossiers.