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AI coding platform and IDE that orchestrates multiple agent sessions and lets teams plug in their own AI subscriptions.
Developer API that gives AI agents persistent memory, retrieval, and connectors, usable both as infrastructure and a personal app.
Free all-in-one desktop AI app to chat with your documents and run RAG and AI agents fully local and private.
Open-source testing platform where AI agents drive your app end-to-end to catch regressions on every PR, no test code needed.
Vertical AI platform delivering industry-specific predictive, generative and agentic applications for retail, finance and industrial firms.
No public pricing
No public pricing
No public pricing
- ✦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
- ✦Persistent, structured memory built as a knowledge graph
- ✦Sub-300ms hybrid retrieval (RAG) with reranking
- ✦Native filesystem mount for agent memory access
- ✦Connectors to Slack, Notion, Drive, Gmail, GitHub, S3
- ✦Automatic extraction from PDFs, images, and audio
- ✦User profile and behavior tracking across sessions
- ✦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
- ✦AI agents navigate your app in real browsers
- ✦One-command setup that maps flows and drafts tests
- ✦SDK to seed and tear down real data
- ✦Runs on every PR against preview deploys
- ✦No test code required
- ✦Open-source with a self-hosted option
- ✦Integrates with GitHub, Vercel and Linear
- ✦Industry-specific AI applications (retail, finance, industrial, IT, media)
- ✦Eureka platform for making enterprise data AI-ready
- ✦Agentic AI agents for tasks like SAR drafting or inventory routing
- ✦Financial-crime alert reduction and investigation tools
- ✦Demand forecasting and shelf/pricing optimization
- ✦Real-time industrial root-cause analysis
- →Shipping code faster with AI agents
- →Coordinating agent work across a team
- →Managing tasks and artifacts in one place
- →Running many parallel agent sessions
- →Developers adding long-term memory to AI agents
- →Teams building agents that need to sync with existing tools
- →Individuals wanting one memory layer shared across multiple AI assistants
- →Privately querying your own documents
- →Running local AI without the cloud
- →Building AI agents over your data
- →Using multiple LLM providers in one app
- →Catching regressions before merging PRs
- →End-to-end testing without writing scripts
- →QA for fast-shipping product teams
- →Self-hosted testing on your own infrastructure
- →Retailers optimizing pricing, inventory and promotions
- →Banks reducing false-positive fraud and AML alerts
- →Manufacturers diagnosing production downtime in real time
- →Enterprises building custom AI agents on their own data