Observe the factory
Normalize bare metal, GPUs, fabrics, schedulers, runtimes, trust state, and business context into a single Factory Graph.
Factory Compiler for AI infrastructure
Compile business intent into safe, auditable, and explainable AI factory decisions. Start with idle capacity elimination. Grow into autonomous factory operations.
Product thesis
AI infrastructure has become a stack of independent operators, schedulers, runtimes, telemetry streams, and business systems. Intelfactory.ai turns that operational sprawl into a typed graph that humans and agents can reason about.
Normalize bare metal, GPUs, fabrics, schedulers, runtimes, trust state, and business context into a single Factory Graph.
Convert requests like reduce cost, improve SLA, or reclaim capacity into Factory IR, policy context, and explainable recommendations.
Produce GitHub-backed change plans with risk, rollback, verification, and human review before execution.
Initial wedge
The first customer is the AI infrastructure team trying to answer concrete questions before buying more GPUs.
Which GPUs are stranded?
Which workloads are overprovisioned?
Which tenants can safely shrink?
Which capacity can be reclaimed without violating policy?
System architecture
The compiler path is intentionally conservative: observe, recommend, review, execute only after policy and approval, then verify and roll back when needed.
Optimization loop
Factory Compiler watches infrastructure, schedulers, runtimes, agents, and business systems as one decision surface. Those signals compile into Factory IR, run through optimization passes, and produce reviewable change plans.
Built for operators