The AI Factory runs at a fixed monthly fee sized to your environment and guardrail footprint. There is no hourly billing and no per-call surcharge. Approved pilots include $10,000 in AWS credits to offset infrastructure during the discovery and foundation phases.

AI Factory | Managed backbone for compliant, production-ready AI

Q: Where do we draw the line between a bespoke agent and an off-the-shelf chatbot?

If the use case depends on your proprietary data, your compliance posture, or your internal domain rules, we build it inside the AI Factory where those constraints live. Generic customer support or content drafting with no sensitive context runs fine on off-the-shelf tools. We help you pick the line on the first scoping call.

Q: How do we pick the first use case?

Use-case selection is the first phase of onboarding. Our team runs a workshop against your product roadmap, ops load, and compliance concerns to surface candidate agents or models. You leave with a prioritised list and an agreed pilot scope, usually inside two weeks.

Q: We run a multi-tenant SaaS. What controls does the Factory give us for tenant isolation?

Private agents and models run under individual engineer identities, not shared service accounts, so attribution is always traceable. The ingestion framework anonymises or tokenises sensitive fields before data leaves production. Customer data never crosses tenant boundaries without an explicit policy rule, which sits in Git.

Q: Can we run the Factory alongside existing DevOps as a Service?

Most of our AI Factory customers already run DevOps as a Service with us. The Factory reuses the same account access, CI infrastructure, and on-call team, so nothing gets double-billed. MLOps in particular is often sold as an add-on at a discounted rate when DevOps as a Service is already in place.

Q: How soon can we get started?

Approved pilots move into discovery within two weeks of sign-off. Onboarding runs in three phases across six to nine weeks, ending with the first agent or model live in production under the managed framework.

The foundation for AI, not another AI solution.

A managed backbone inside your AWS accounts with 60+ guardrails, audit trails, and 24/7 operations. Your team ships AI features. Ours runs the platform underneath.

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What the Factory gives you

Compliance by Design

Sixty-plus guardrails mapped to ISO 27001, SOC 2, and CPS 234. Version-controlled in Git, maintained by our team. Evidence packs export for audit.

Data Protected at Source

The ingestion framework anonymises sensitive fields before anything reaches non-production. Private agents and models run under your engineers' identities. No shared accounts, no IP leakage.

Proof for Stakeholders

Real-time dashboards and evidence lakes show regulators, boards, and investors that your AI is under control. You get the proof the moment they ask.

Agentic Ops

Secure, autonomous agents that run inside your boundary. Persona-based, version-controlled prompts, audit trails for every interaction, misuse detection built in. Your developers stop doing things differently across the codebase.

Explore Agentic Ops →

What you get

Persona library Coding, compliance, support personas with shared prompts.
Audit trail Every prompt, response, and action logged and reviewable.
Misuse detection A recommendation agent flags patterns before they ship.

Guardrails

The managed control framework underneath the Factory. 60+ enforced guardrails across data protection, access, accuracy, cost, and regulatory alignment.

See the controls →

MLOps

Reproducible pipelines, retraining, drift monitoring, and accuracy dashboards for data science teams. Add-on for customers training custom models.

See MLOps →

How we roll it out

Onboarding runs six to nine weeks across three phases, then the Factory moves into ongoing managed operations.

Discovery

One to two weeks. Scoping workshop, risk and data assessment, first-use-case selection, pilot scope agreed.

Foundation

Two to three weeks. Factory deployed inside your AWS. Guardrails, evidence pipelines, and operator tooling live. Dashboards wired up.

Deployment

Three to four weeks. First agents or models shipped into production with monitoring and audit from day one.

Operate

Ongoing. 24/7 managed operations, guardrail updates, patching, and a monthly service review with your team. Fixed monthly fee.

Audited and certified

AWS DevOps Competency

ISO 27001 Certified

AWS SaaS Competency

See what the Factory covers in your environment.

Approved pilots include $10,000 in AWS credits. Walk us through your setup and we will show you what the first 30 days look like.

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Frequently asked questions

Where do we draw the line between a bespoke agent and an off-the-shelf chatbot?

If the answer needs your data, your compliance posture, or your domain rules, you build inside the Factory. Everything else, use off-the-shelf.

How do we pick the first use case?

We start with a scoping workshop that finds the highest-value, lowest-risk agent or model. You leave the first session with a prioritised list.

We run a multi-tenant SaaS. What controls does the Factory give us for tenant isolation?

Every agent runs under an engineer identity, not a shared account, and the ingestion framework anonymises sensitive fields before they reach non-production.

What does it cost?

Fixed monthly fee for the managed Factory. Pilots include $10,000 in AWS credits.

Can we run the Factory alongside existing DevOps as a Service?

Yes. AI Factory is designed as an add-on to DevOps as a Service and shares the same account access and on-call team.

How soon can we get started?

Approved pilots move into discovery within two weeks. First agent or model live in six to nine weeks.

The AI Factory on AWS

The guardrails that make AI secure, compliant, and ready for scale on AWS. A managed backbone with 60+ controls, audit trails, and 24/7 operations. Runs inside your own tenancy.