Sub-offering

ML Ops as a Service

A managed lifecycle platform delivering CI/CD, continuous monitoring, drift detection, automated retraining and pre-configured cloud & edge infrastructure — under Qatar's Responsible AI governance.

View deployed models Register a new pipeline

Pipeline

Stage 01

Build

Git commit triggers container build + SBOM + signing

Stage 02

Test

Automated evals, bias & compliance gates

Stage 03

Stage

Canary deploy to staging with A/B routing

Stage 04

Deploy

GitOps promotion to production or edge

Stage 05

Monitor

Drift, guardrails, cost & performance dashboards

Stage 06

Retrain

Auto-triggered pipelines, rollback on regression

Capabilities

CI/CD for ML

GitOps deployments (Flux / ArgoCD), IaC, SBOM & signed container images.

Containerised serving

OpenAI-compatible REST + streaming, GPU autoscaling, multi-model routing.

Real-time monitoring

Accuracy, latency, throughput — with alerting on deviations.

Drift detection

Data and concept drift with configurable thresholds and dashboards.

Automated retraining

Triggered by new data, drift, or performance thresholds.

Guardrails

PII redaction, jailbreak defence, toxicity filtering, content moderation.

Audit & lineage

Full traceability of who deployed what, when and under which policy.

End-of-life

Decommissioning workflows with retention and historical access.

Uptime SLO

99.95%

Inference endpoints (P0 tier)

Latency p95

≤ 120 ms

Real-time text & vision serving

Compliance

100%

Audit pass rate — Responsible AI charter