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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.
Agentic coding platform (Cosmos) that runs software-dev agents at org scale, using a codebase context engine to cut token cost.
Vertical AI platform delivering industry-specific predictive, generative and agentic applications for retail, finance and industrial firms.
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- ✦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
- ✦AI-powered trading indicators
- ✦Screeners for identifying high-probability setups
- ✦Backtesters for strategy optimization
- ✦AI Backtesting Assistant for automated strategy building
- ✦Community support and educational resources
- ✦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
- ✦Context Engine for codebase understanding
- ✦Agents across the full SDLC
- ✦Model routing / bring-your-own-keys
- ✦Automated code review and test coverage
- ✦CLI, MCP and native tool integrations
- ✦Enterprise security (SOC 2, ISO 42001, SSO)
- ✦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
- →Automating complicated price action analysis
- →Generating trading signals and detecting reversals
- →Scanning assets for specific trading criteria
- →Backtesting and optimizing trading strategies
- →Building trading strategies with AI assistance
- →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
- →Automating PR code review
- →Raising test coverage
- →Incident investigation and remediation
- →Large-scale migrations and onboarding
- →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