Claude services · Customer-Facing AI Product Build
Claude built into your customer-facing product, with evaluation, safety, and cost controls.
We design the production architecture, build the capability inside your codebase and release process, add evaluation suites and a safety layer, model the unit economics, and support the launch.
- Engagement
- Scoped to a fixed fee
- Fixed scope
- Typical timeframe
- 3–6 months
- Who it's for
- Product and engineering teams shipping an AI capability to their own customers, where quality and cost are commercial risks.
- What you walk away with
- A Claude-powered product capability live for your customers, with evaluation and cost control in place.
What you get
What we deliver.
- Product and technical discovery: the capability, its quality bar, and its unit economics
- Architecture for production: streaming, caching, model routing, fallbacks, and rate limits
- The build itself, integrated into your product and your release process
- Evaluation suites and quality gates tied to the behaviour your customers see
- Safety layer: abuse handling, prompt-injection defences, content policy, and escalation paths
- Unit-economics model and cost controls so margin holds as usage grows
- Instrumentation, launch support, and a documented operating runbook
In practice
- 01An AI assistant inside a SaaS product, built against a real quality bar
- 02Claude-powered drafting or review added to a professional-services platform
- 03An existing AI feature rebuilt because quality or cost didn't hold at scale
Scope
What you need, and what is not included.
What you'll need
- A product owner and access to your engineering team and codebase
- A defined customer-facing use case
- Agreement on the quality bar and the cost envelope before build
Not included
- Anthropic consumption costs or your own infrastructure costs
- Product marketing, pricing strategy, or go-to-market
- Ongoing production operations (that's Managed AI Operations)
The engagement
- 01Step 1
Discovery and architecture, including the quality bar and cost envelope
- 02Step 2
Milestone build inside your codebase and release process
- 03Step 3
Hardening: evaluation, safety, load and cost testing before exposure
- 04Step 4
Staged launch, instrumentation review, and handover with a runbook
- An Anthropic Select Partner with Claude-certified architects. The people who scope your programme are the people who build it.
- 50+ specialists across strategy, implementation, automation, data, and custom development, so the Claude work is connected to the systems you run.
- Every engagement ends with training and documentation, so your team runs it without us.
Questions
Frequently asked questions.
Can you work inside our codebase and process?
Yes. That is the default. We work in your repositories, your review process, and your release cadence, so what ships can be maintained by your team.
How do you keep the cost per customer under control?
Model routing, prompt caching, context discipline, and hard usage limits, modelled against your pricing before the build and instrumented after launch so margin is visible per customer.
How do you handle prompt injection on customer input?
Untrusted input is treated as data, never as instructions: constrained tool surfaces, output validation, privilege separation between the model and your systems, and adversarial tests in the evaluation suite.
Who pays for Claude licences?
Anthropic seats and API consumption are billed to you on your own account, so the environment and the data stay yours. We help you land on the right plan and model mix as part of the engagement.
Next step
Book a discovery call.
Tell us where you are with Claude and what you want from Customer-Facing AI Product Build. You leave the call knowing whether it fits and what the fixed-fee proposal will cover.
30 minutes. No commitment.