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AI copilot for product managers: turns ideas into PRDs and specs, gives CPO-style feedback, and integrates with PM tools.
Open-source React/Angular SDK and platform for embedding agentic, generative-UI copilots into apps, Slack and Teams.
High-performance open-source vector database for production AI retrieval and RAG, for teams needing scale, hybrid search, or self-hosting.
Fully managed AI search infrastructure with built-in RAG, letting developers add multimodal search via simple APIs.
Enterprise Agentic RAG platform (now under Progress) unifying data into a knowledge layer for AI agents and LLMs.
Free trial available
No public pricing
No public pricing
Free trial available
- ✦Generate PRDs, one-pagers and user stories from a prompt
- ✦CPO-level document coaching and gap analysis
- ✦Custom templates matched to team standards
- ✦Integrations: Linear, Notion, Slack, Confluence, GitHub
- ✦Shared team workspaces and personas
- ✦Export to Notion, Confluence, Google Docs
- ✦React and Angular frontend SDKs
- ✦Agent-rendered generative UI
- ✦AG-UI agent-user interaction protocol
- ✦Connectors for LangChain and other frameworks
- ✦Pre-built customizable chat/sidebar components
- ✦Slack and Teams integrations
- ✦Thread and state persistence
- ✦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
- ✦Managed AI search with RAG
- ✦Multimodal search (text, images, PDFs)
- ✦Automated chunking and multi-stage reranking
- ✦Advanced metadata filtering
- ✦Python and TypeScript SDKs
- ✦Zero-setup developer-first APIs
- ✦RAG-as-a-service and modular RAG
- ✦NucliaDB knowledge store
- ✦Generative AI ingestion of unstructured data
- ✦Agentic knowledge layer for AI agents
- ✦RAG evaluation (REMi) and Prompt Lab
- ✦Model Context Protocol support
- →Draft product requirement docs fast
- →Get expert feedback on specs
- →Standardize docs across a product team
- →Turn PRDs into tickets and prototypes
- →Adding an AI assistant to a SaaS product
- →Building agents that render interactive UI
- →Deploying copilots across Slack and Teams
- →Connecting existing agents to a frontend
- →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
- →Adding AI search to a product
- →Building RAG features without infra work
- →Searching across mixed content types
- →Building enterprise copilots and assistants
- →Generative search over company data
- →Video and document indexing
- →Powering AI agents with governed knowledge