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Side-by-side features, use cases and pricing — because the right pick depends on your job and budget, not just the ranking.
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Free all-in-one desktop AI app to chat with your documents and run RAG and AI agents fully local and private.
High-performance open-source vector database for production AI retrieval and RAG, for teams needing scale, hybrid search, or self-hosting.
AI coding platform and IDE that orchestrates multiple agent sessions and lets teams plug in their own AI subscriptions.
Developer API suite (Reader, Embeddings, Reranker) that turns web content into LLM-ready data for search and RAG.
Voice-AI platform offering real-time text-to-speech, speech-to-text and voice-agent models through one API.
No public pricing
No public pricing
No public pricing
No public pricing
- ✦Chat with your documents (RAG)
- ✦Runs locally and offline for privacy
- ✦Supports any LLM (local or cloud)
- ✦Built-in AI agents
- ✦Handles PDFs, Word, CSV, codebases
- ✦No-code setup
- ✦Hybrid dense and sparse vector search (BM25, SPLADE, miniCOIL)
- ✦Advanced metadata filtering applied during search traversal
- ✦Multivector support for multimodal retrieval
- ✦Reranking with score boosting and late-interaction models (ColBERT, MMR)
- ✦Flexible deployment: cloud, hybrid, private, or edge
- ✦Rust-based engine optimized for low-latency, high-scale search
- ✦AI coding IDE with agent orchestration
- ✦Run and manage multiple agent sessions
- ✦Task, artifact and collaboration tools
- ✦Bring-your-own AI subscription or API keys
- ✦Cloud-scale agent execution
- ✦Reader API converts URLs to Markdown
- ✦Multimodal multilingual embedding models
- ✦Reranker for stronger search relevance
- ✦Web search endpoint returning SERP data
- ✦MCP server for use inside LLMs
- ✦Native inference inside Elasticsearch
- ✦Sonic real-time text-to-speech
- ✦Ink speech-to-text
- ✦Line voice agents
- ✦Low-latency real-time output
- ✦Voice cloning
- ✦Single multilingual API
- →Privately querying your own documents
- →Running local AI without the cloud
- →Building AI agents over your data
- →Using multiple LLM providers in one app
- →Building retrieval-augmented generation (RAG) pipelines
- →Powering AI recommendation and semantic search systems
- →Enterprises needing on-prem or hybrid deployment for compliance
- →AI agent platforms needing fast contextual retrieval at scale
- →Shipping code faster with AI agents
- →Coordinating agent work across a team
- →Managing tasks and artifacts in one place
- →Running many parallel agent sessions
- →Ground LLMs with clean web content
- →Build semantic and RAG search
- →Rerank retrieved results
- →Give AI agents live web access
- →Building voice agents
- →Text-to-speech and transcription apps
- →Fraud-detection verification calls
- →Real-time customer support voice