Projects
AI Ecosystem — specialized platforms that compose into something greater than the sum of their parts
CortexObserver
The Natural-Language Command Layer for an AI Workforce
The flagship — an Agentic & Ecosystem Command-and-Control platform that absorbs every project below into one governed system. Direct 10 specialized AI agents in plain English to deploy cloud infrastructure, train ML models, and run trading research — each operating inside human-set policies, budgets, risk limits, and approval gates. Commander for natural-language dispatch, A.T.O.M for the live AWS estate and CloudFormation dependency graph, five governed Farms, and a full governance loop: humans write the rules, agents do the work, and every outcome renders live.
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Commander.ai
Multi-Agent AI Orchestration Platform
Multi-agent AI orchestration platform enabling intelligent task automation through coordinated agent networks. Built with LangGraph for state management and agentic workflows. Features 8 specialized agents, live prompt engineering, NLP scheduling, performance analytics, and real-time streaming SSE responses.
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WorldMaker.ai
Enterprise Digital Lifecycle Intelligence
Enterprise Digital Lifecycle Intelligence platform providing comprehensive digital transformation analysis and code generation. Features 22 integrated views, 41 REST endpoints, and extensive test coverage across 6 languages and 24 framework code generation targets.
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ml-pipeline.ai
Autonomous ML Pipeline — Raw Data to Trained Model
Fully autonomous machine learning pipeline powered by LangGraph that takes raw data and plain-English objectives, then executes the entire ML lifecycle — profiling, feature engineering, visualization, model training, evaluation — with an LLM-powered Critic that reviews results and iterates until quality thresholds are met. No notebooks. No manual tuning. Just outcomes.
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MCPFarm.ai
Kubernetes for AI Tools — Centralized MCP Governance
Docker-based platform that orchestrates, discovers, and exposes multiple MCP servers through a unified gateway with real-time dashboard, Python SDK, and tool-level analytics. Brings Kubernetes-style governance to the Model Context Protocol ecosystem — centralized control over which AI tools are available, who can access them, and how they perform.
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ProblemSolver.ai
Five-Agent Reasoning Pipeline with Autonomous Revision
Multi-agent reasoning pipeline powered by LangGraph that decomposes complex problems through five specialized agents — Thinker, Planner, Critic, Solver, Judge — with 15 tools across research, analysis, code, math, and documents. Autonomous revision loops iterate until quality thresholds are met.