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Move AI From Pilot To Production.
99% of firms plan agentic AI in production; 11% have shipped it. The blocker is the platform underneath, not the model. The AI Factory delivers the platform, the governance and the modernization as one managed solution — on infrastructure your regulator already accepts.
The bottom line.
Financial firms aren't short on AI ambition. 99% plan to put agents into production; only 11% have. Gartner expects 40% of agentic projects cancelled by 2027 — because the governance fails first, not the model. The pilots are stuck on the platform underneath.
The AI Factory is one managed solution for that: Options Modern Cloud with AI AgentOps for governed agents, PrivateMind for GPU and sovereign models, and MigrateIQ to turn the legacy estate into agent-callable services — operated in 70+ data centres, including the venues where the exchanges run.
Why now.
The Pilot-To-Production Gap
99% plan agentic AI in production; 11% have shipped it. Gartner sees 40% of projects cancelled by 2027. The blocker is governance, not models.
Governance Fragmentation
Hyperscalers sell agent gateway, guardrails and observability as separate services. You integrate four-to-six pieces and pay egress between them.
Regulatory Expectation
DORA Article 28, NYDFS 500, FFIEC, SR 26/2 and SEC 17a-4 now all reach AI workloads — governance has to be attached at the platform layer.
Capacity Locked In Legacy
VMware-era and legacy-JVM stacks tie up compute and memory — up to 5x compute and 10x memory. That freed capacity is what AI needs to run.
The Citizen-Developer Surge
Builders spread far beyond IT — analysts, ops, risk, research. Without a safe, sanctioned place to build, shadow AI is the default.
The strategy.
Where It Applies
- Regulated firms with AI experimentation but nothing yet in production at scale
- Substantial VMware, legacy-Java, Oracle or on-prem Microsoft estates
- Hedge funds, asset managers, banks, broker-dealers, exchanges, custodians, FSI ISVs
- At least one operational use case in mind — ops, KYC, fraud, reconciliation, copilots
Honest Edge Cases
- No AI ambition in the next 12–18 months — the Factory isn't the conversation yet
- Committed to a single-hyperscaler AI strategy and comfortable with the trade-offs
- Fully-managed SaaS, no on-prem workload, no plan to bring AI inside your perimeter
One Factory. Three operated products.
One managed solution, not four point products you integrate and pay egress between. Three operated layers, one accountable operator.
Options Modern Cloud with AI AgentOps
OpenShift hardened for FSI, with agent guardrails, observability and audit built in at the platform layer.
PrivateMind
GPU infrastructure-as-a-service and Model-as-a-Service, so inference runs on capacity you control, inside your perimeter.
MigrateIQ
Refactors the legacy estate into API-first, agent-callable services, with governance built in at the contract level.
How it runs on OMC.
The Factory is built on Red Hat OpenShift AI, operated by Options in the data centres where your trading and post-trade workloads already run. The tier you pick changes worker isolation, not the foundation.
Standard
Shared, multi-tenant OpenShift under one Options compliance policy. Code-ready on day one.
Advanced
Dedicated worker pools with GPU-backed namespaces, host control-plane isolation, and your CI/CD or ours.
Dedicated
Single-tenant bare metal, designed in — GPU passthrough and sovereign AI on silicon you control.
PodOps managed service
Options FSI hardening
Red Hat OpenShift
Kubernetes
The discovery & design session.
The first step is a 90-minute executive session — not a pitch. We work through four dimensions and a first cut of a Factory designed for your estate. A short prerequisite pack beforehand keeps the 90 minutes on your firm, not table stakes.
- ✓ Your current environment — VMware, cloud, apps, data and connectivity
- ✓ Your goals — the next 12–24 months, and where AI fits
- ✓ Your AI strategy — pressure-tested, or framed if you need one
- ✓ A custom Factory — platform sizing, modernization sequence, governance
You leave with a defensible answer on whether the Factory is right for you — and if it is, the outline of one designed for your firm.
From decision to steady state.
If the session ends in a decision to proceed, the engagement runs in three phases — each justifies itself before the next begins.
Architecture & Roadmap (4–6 wks)
A binding architecture and phased roadmap: platform, GPU, modernization sequence, AI AgentOps governance, compliance mapping and a commercial proposal.
First Production Workload (8–16 wks)
The first agent in production against a modernized service — governed by AI AgentOps, observable in your tooling, audited to your records systems. PodOps runs it 24/7.
Scale To Steady State (12–24 mo)
Modernization waves and agent use cases in parallel. Freed compute absorbs AI growth; the cost line drops as the capability expands.
Proof and business case.
Four levers — productivity, operations capacity, agentic ROI, and compute recovered from modernization — where the modernization savings fund the AI growth. Your numbers come from Phase 1.
On the same Red Hat OpenShift AI stack, DenizBank cut new-model time-to-market from about a week to minutes across 120+ data scientists (public Red Hat reference).
Red Hat Premier partner · 5× Container Platform Specialist of the Year · globally exclusive Application Platform Specialization
Ready to ship AI?.
Pairs with AI & PrivateMind. Also stacks with Public Cloud Repatriation and Oracle → EDB.