Ship a production generative AI feature.
A scoped consulting engagement that designs and ships a real GenAI capability inside your AWS account. RAG systems, autonomous agents, or a custom model fine-tuned to your domain. Engagement-based, fixed scope, clear handover.
Your engineers run it afterwards. We stay available for ongoing uplift if you want the AI Factory.
What you get
Scoped GenAI build
One production feature, end to end. RAG, agents, custom model, or a hybrid. Scoped to an outcome, not an hour count.
Inside your AWS
Built under your account, your IAM, your data residency. We never host or hold your model or data.
Domain-tuned
The build reflects your domain language, your customers, and your product, not a generic demo.
Responsible by default
Guardrails, audit logging, and content controls baked into the build. Inherits the AI Factory patterns where relevant.
Handover planned from day one
Engineers shadow-pair through discovery, design, and build. By launch, your team can extend and operate it.
Clear next step
Run it yourself, add DevOps as a Service, or move to the AI Factory for ongoing managed operations. Your call at handover.
Engagement-based. Fixed scope. Knowledge transfer.
Discovery
- Use-case workshop
- Data and compliance review
- Success criteria agreed
- Benchmarks chosen
- Scope locked
Design
- Architecture in your AWS
- Model and tooling selection
- Prompt and retrieval design
- Evaluation harness
- Guardrail policy
Delivery
- Production feature shipped
- Evaluation suite running
- Documentation
- Training
- Signed-off handover
How it works
A consulting engagement is not open-ended. Each phase has a clear output. You own everything we produce.
Discover
Use-case workshop, data audit, compliance check, success criteria, and scope agreement. Clear input to Design.
Design
Architecture, model selection, prompt strategy, retrieval design, evaluation harness, and guardrail policy. Reviewed before build starts.
Build
Feature built in your AWS. Evaluation suite running throughout. Your engineers paired in from the start.
Handover
Production feature signed off. Documentation, training, and a clear path forward, whether self-run or AI Factory.
Audited and certified
AWS DevOps Competency
ISO 27001 Certified
AWS SaaS Competency
Pick the GenAI feature that matters. We will scope the build.
Walk us through your product and the capability you want to ship. We will scope an engagement on the first call.
Frequently asked questions
What kind of generative AI build is this for?
Production features: RAG systems, autonomous agents, custom fine-tuned models, or content-generation workflows. Not POCs and not demos.
Which models and providers do you work with?
Bedrock, Anthropic, OpenAI, and open-weights models hosted in your AWS. Selection is based on your data, latency, cost, and compliance needs, not vendor preference.
How long does an engagement take?
Typical engagements run eight to sixteen weeks depending on feature complexity and data readiness.
Do you build bespoke agents or use off-the-shelf frameworks?
We favour frameworks that match your stack: LangChain, LlamaIndex, Bedrock Agents, AWS Strands. Bespoke only when the requirement genuinely warrants it.
Where do prompts, evaluations, and code live?
In your Git repositories and your AWS account. We deliver into your infrastructure, not ours.
What happens if we want ongoing operations?
Add the AI Factory. Agentic Ops runs the agents, Guardrails enforces controls, MLOps handles any custom-model lifecycle. The consulting engagement hands off cleanly into managed operations.