Two engineers review code together on large monitors

Practice · Platform Engineering

Engines that power AI outcomes.

One governed AI platform on the clouds you already use, with security built in from the first environment.

See the Brightside Health story

Why now

AI is multiplying. One platform lets it scale safely.

Every team and cloud now runs its own models. A shared foundation keeps cost and risk in view as that grows.

One governed control plane.
Models, agents and data managed in one place, across every team and cloud.
Guardrails by design.
Responsible AI and security built in from the first workload.
Innovation with confidence.
Teams move quickly while risk stays inside the limits your enterprise sets.
Open to every team.
The whole organization builds safely on one shared foundation.

Capabilities

Everything your AI products stand on.

The AI platform every product runs on, and the foundation, migration and operations under it.

AI platform
One governed engine for every AI product.
Enterprise architecture and technical design
Design the target state before anything moves.
Cybersecurity and threat modeling
Build the controls in, not on.
Cloud landing zone for regulated workloads
Build the regulated foundation once.
Migration and modernization
Move the workload, and leave a pattern.
DevOps and developer platform
Make the approved way the fastest way.
See the developer hub
Run and improve
Keep it healthy after launch.

Where you start

Every team starts from a different step.

AI maturity differs from company to company, and from team to team inside one company. We start at the step each team has reached and take the work to production.

50%By the end of 2025, at least 50% of generative AI projects were abandoned after proof of concept.Gartner, January 2026

Step 01
Exploring
Many AI ideas and migration options, no ranked priorities, and leaders not yet aligned.
CWX enters atAI Value Accelerator1 to 1.5 weeks
Step 02
Piloting
A clear priority, and leadership wants proof of ROI before it funds the build.
CWX enters atProof of value sprint2 weeks
Step 03
Executing
A named sponsor and a budget, but workloads and use cases are not yet in production.
CWX enters atProduction build2 to 3 months
Step 04
Scaling
A few workloads and use cases live, and one-off wins are not yet spreading.
CWX enters atScale, by value chainOngoing

Every step moves the work closer to production, and you decide when to take the next one.

We engage at the stage you have reached, and we are measured on your outcome from there.

What our forward deployed teams deliver

Four kinds of work, one team.

Migrations
Regulated workloads and legacy platforms
Dependencies mapped first, then rehost, replatform or rebuild in waves, with the legacy stack retired.
Inside the Migration Factory
Platform Engineering
Cloud foundation
Secure multi-tenant foundation, advanced hybrid networking, infrastructure as code, policy guardrails and cost governance, with self-service provisioning for lines of business.
See the AI platform
Data AI/ML
Data platforms and models
Batch and streaming ingestion from core systems, processing at enterprise scale, lakehouse modeling, governed BI and ML data.
Explore Data AI/ML
New products and use cases
Governed AI, launched
New products launched with agentic AI that meets the governance and compliance bar of regulated industries.
Explore AI Engineering

Security and compliance in all four. Controls mapped to your framework, policy-as-code enforcement, encryption and key management, privileged access.

Forward Deployed Strategists map the estate and agree the controls with your security team. Forward Deployed Engineers build the platform once, migrate in waves and hand it over. See how Forward Deployed Teams work

Where this shows up: Decision Speed and Oversight.

The Migration Factory

The Migration Factory, in six phases.

One method for every migration, with AI and agentic AI at every phase.

Six phases, AI in every one

From an estate with no documentation, hidden dependencies and tightly coupled monoliths, to workloads that are migrated, modernized, compliant and cloud-native.

Phase 0
Govern
The operating model, financial baseline and governance that steer the program.
- Automated TCO and risk
Phase 1
Discover
The true as-is estate, captured automatically: no spreadsheets, no tribal knowledge.
- AI discovery and code scan
Phase 2
Foundation
A secure foundation before migration: remediate the landing zone, or build one in parallel.
- AI security posture
Phase 3
Rationalize
The right move for every application, sequenced into dependency-aware waves.
- Agentic 7 Rs disposition
Phase 4
Implement
Build, migrate and modernize each wave. Pods own delivery, and AI takes on the repetitive build, refactor and test work.
- Generative AI build, refactor and test
Phase 5
Cutover
Cut over with downtime planned to the minimum, validate, and hand a fully documented estate to Day-2 operations.
- AI runbooks and monitoring

Faster
agentic discovery, code analysis and generative build take out much of the manual work.
Safer
AI security-posture reviews and automated guardrails are built into every wave, with evidence for each control owner.
Smarter
evidence-based 7 Rs disposition, every move backed by code, dependency and currency analysis.

Proof