Composable AI infrastructure with model risk built in.
Reference architectures, accelerators, and runbooks for enterprises building AI platforms in regulated environments.
What ships with AI Platforms.
Reference architectures
Cloud-specific blueprints for AWS, Azure, GCP, on-prem, and sovereign deployments.
Model gateway & router
Multi-provider routing, fallback, cost optimisation, content policy enforcement.
Vector & retrieval infra
Tested patterns for OpenSearch, pgvector, Weaviate, Pinecone — chosen for your scale.
Evaluation & red-team harness
Continuous evaluation, drift monitoring, automated red-teaming.
Model risk management
SR 11-7 / equivalent record-keeping, kill-switch, regulator-facing reports.
Cost & FinOps for GPUs
GPU pool management, batch optimisation, commitment planning.
Built for the audit, not the demo.
Cloud-native
Container-first, autoscaling, multi-region. Deployable on AWS, Azure, GCP, OCI, or your VPC.
Open and composable
API-first. Webhooks. SDKs. We do not believe in lock-in — switching cost should be a feature.
Governed by default
RBAC, audit logs, lineage, policy-as-code. Audit packs available under NDA.
Outcomes you can hold us to — by horizon.
Foundations
Outcome tree, baseline metrics, and a working pilot in production by day 90 — defensible with finance, signed off by risk.
Scale
Squad expansion across the next 2–3 value pools. Live-parallel cutovers. Capability uplift inside the client team.
Run & optimise
Managed run with named SLOs, quarterly value reviews, and a continuous-improvement budget reserved for innovation, not toil.
Where AI Platforms is running.
AI underwriting
9 days → 14 minGCC sovereign bank deploys AI underwriting in 11 months
Read case studyDocument AI
6d → 4hIdentity authority deploys AI document intelligence — passport processing 6 days → 4 hours
Read case studyTax compliance AI
+SAR 2.1BMiddle East Tax Authority deploys AI tax compliance scoring — recovery +SAR 2.1B
Read case studyThree commercial models. One outcome standard.
We avoid open-ended retainers. Every model names its outcome and its measurement window in the contract.
Fixed-price diagnostic
2–4 week engagement. Outcome tree, baseline metrics, prioritised value pools, and a board-ready 18-month roadmap. Stop-go decision in week 4.
Outcome-linked pilot
8–12 week engagement to ship one value pool, end-to-end, with a measurable KPI commitment. Joint squads with the client team. Live-parallel before cutover.
Programme + managed run
Multi-quarter scale-out with managed services on top. Quarterly value reviews. SLO-tied annual incentive. Capability transfer by design.
Frequently asked questions
How is this priced? +
Per-seat for HR/Desk; per-workload for Hub/Lend/AI/Data. Volume tiers and commitments available. We avoid surprise overages.
Can it run on-prem / sovereign cloud? +
Yes. We have shipped sovereign deployments in three jurisdictions.
Open source? +
Mixed — many of the building blocks are open source; the platform itself is commercial. Source-available terms available for some clients.
Will you customise it? +
Within reason. Our architecture is designed for extension, not customisation. Most customer-specific work goes into composition, not core.
How does it integrate with our stack? +
120+ pre-built connectors, plus REST/GraphQL/webhook integration patterns. We integrate with your IdP, observability, and ticketing.
Migration path from incumbent? +
We have migration patterns for common incumbents. Discovery / migration scoping in 2 weeks.
See AI Platforms on your data, in 30 minutes.
A platform partner walks you through the relevant capability — and answers the hard procurement questions.