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DC Energy Intelligence
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Technical Documentation

Tier-0 Cognitive Energy OS Framework

A domain-specific architecture combining RAG, fine-tuned reasoning, formal planning, constraint solvers, and external verifiers targeted at facility energy, cooling, and AI workload orchestration.

Primary Optimization Objectives

The framework optimizes across five critical dimensions, balancing competing priorities through multi-objective optimization.

Cost

Energy spend, demand charges, peak shaving

Carbon

CO2e per job/request, carbon-aware shifting

Reliability

Electrical/thermal envelopes, N+1 constraints

Performance

SLA/SLO for inference, time-to-completion

Compliance

Audit-ready metering, allocation, reporting

Reference Architecture Pipeline

An eight-stage pipeline from data ingestion to auditable execution.

Sense
Normalize
Attribute
Plan
Optimize
Verify
Execute
Audit
Data Plane (Telemetry + Context)
  • Electrical: UPS/PDU/RPP meters, branch circuits, generator fuel
  • Cooling: Chillers, CRAH/CRAC, pumps, economizers, valve positions
  • IT: Node power (Redfish/IPMI), GPU telemetry (NVML/DCGM), CPU/mem, job metadata
  • Environment: Rack inlet temps, humidity, hotspots
  • Market: Tariff, demand charges, TOU pricing, carbon intensity, DR events
  • Topology: One-line diagrams, feeder capacities, redundancy state
Knowledge Plane (RAG Corpus)
  • FACILITY_TOPOLOGY: Feeders, PDUs, rack mapping, redundancy state
  • LIMITS_POLICY: Thresholds, safety margins, max caps
  • SCHEDULER_POLICY: Priorities, preemption rules, deadlines
  • TARIFF_MODEL: TOU rates, demand charge rules, DR triggers
  • CARBON_INTENSITY: Grid mix by region/time
  • INCIDENT_KB: Known failure modes, prior root causes, mitigations
  • HARDWARE_KB: Power curves, thermal limits, recommended caps

External Verifier Suite

Seven non-negotiable gates that every output must pass before execution. If any verifier fails, the system regenerates or escalates to human review.

1

Schema/Contract Validator

All outputs match JSON schema; no missing required fields

2

Electrical Envelope Checker

Proposed plan cannot exceed feeder/PDU/rack limits (with safety margins)

3

Thermal Guardrail Checker

Plan respects predicted rack inlet temperature bounds + hotspot risk threshold

4

SLA/SLO Validator

Inference capacity and latency budget preserved

5

Change Risk / Blast Radius

Any facility setpoint change requires explicit risk classification and rollback plan

6

Numerical Sanity

kW/kWh/unit checks, monotonicity, bounds, unit conversions

7

Audit Logger

Persist inputs used, assumptions, plan, verifier outcomes, final actions

Policy Enforcement

If any verifier fails, the system will either regenerate the output with corrected parameters or escalate to human review. No unverified outputs are permitted to reach execution.

Control Surface

The framework operates across IT, facility, and contract domains with appropriate levels of automation and human oversight.

IT Side
  • Schedule/queue/migrate batch jobs
  • Set GPU power caps/clocks
  • Consolidate/hibernate nodes
  • Autoscaling guidance
Facility Side
  • Recommendations by default
  • Human-in-the-loop approval
  • Optional BMS/EMS setpoint writes
  • Safety-first approach
Contracts
  • Enforce hard safety limits
  • Feeder, UPS, PDU constraints
  • Rack inlet temp limits
  • Redundancy mode enforcement

Ready to Apply the Framework?

Generate production-ready analysis requests that leverage the full power of the Tier-0 Cognitive Energy OS framework.