Enterprise AI efficiency,
continuously measured.

Metergrade identifies inefficient AI workloads, validates better configurations against your quality requirements, and turns proven improvements into deployment-ready cloud policies.

Calibration field · Workload group 07Candidates C-116 – C-118

31.8% lower inference cost. Quality remained inside threshold.

Seven workloads are operating above their validated cost range.

Test the change before you deploy it.

The control plane
01

Observe

Connects to your existing AI infrastructure and establishes a workload-level economic baseline.

02

Analyze

Detects inefficient model choices, excessive context, output waste, retries and routing issues.

03

Validate

Tests proposed changes against your own quality, latency and reliability requirements.

PASS, FAIL or INCONCLUSIVE. Never a blind recommendation.

04

Deploy

Turns validated improvements into cloud-native configuration: APIM policies, Bicep, Terraform.

05

Govern

Continuously measures cost, quality, drift, policy compliance and realized savings.

How it works

Works with the estate you already own.

Metergrade extends Azure API Management and the Azure AI stack. Telemetry flows in, validated configuration flows back. Nothing new sits in your request path.

APPLICATIONSAZURE API MANAGEMENTAZURE OPENAIAZURE AI FOUNDRYOTHER ENDPOINTSTELEMETRYAPIM POLICIES · BICEP · TERRAFORMMETERGRADEOBSERVEANALYZEVALIDATEDEPLOYGOVERN
The grade

What grade is your AI infrastructure operating at?

Every workload in your estate is operating at some grade right now. Most organizations cannot state it. A Metergrade assessment establishes the baseline across six dimensions and returns an evidence file, not a slide.

AI Workload FitnessWorkload Group 07 · MG-84A2-7721
ECONOMICSA
QUALITYA
LATENCYB+
EFFICIENCYC
CONTROLB
EVIDENCEA−
OVERALLB+
ENV PRODUCTION · VALIDATED 2026-08-02MG / VERIFIED

Runs on the Azure estate you already own.

Metergrade extends Azure API Management with workload economics, quality-validated optimization and continuous efficiency governance.