Conscious Decisions
for AI Compute
SIGURAI is built to reduce unnecessary compute, save energy, and preserve quality by governing the moment before expensive AI execution happens.
Intent
Gate
Signal
Guard
Trail
Core
The layer before execution.
Not another chatbot. Not another dashboard. SIGURAI is a control surface for deciding what compute deserves to happen.
Saves energy
Designed to reduce wasteful model calls, repeated work, unnecessary retries, and excessive agent execution.
Preserves quality
Decisions are constrained by quality gates, evidence records, and conservative execution boundaries.
Records evidence
Every important compute path can become a traceable record: request, decision, runtime call, measurement, and result.
Works with the local AI stack.
Built around local-first execution, model gateways, GPU measurement, and controlled experiments.
Local model execution through a governed gateway.
GPU energy counter contracts and clean measurement windows.
Stable result shape before UI, reports, and evidence.
Runs write job result, runtime calls, and manifests.
Future adapter path for compatible model servers.
Future scale-out control and multi-machine experiments.
From local compute to governed intelligence.
The goal is simple: AI systems should not spend power, time, and money without a conscious decision layer.
Agents
Model calls, tool calls, retries, branches, verifiers, and workflow steps.
Runtimes
Local models today. Open runtimes, inference servers, and accelerated stacks next.
Machines
From one workstation to a lab of overlapping machines, workloads, and GPUs.