Custom AI Product Development
From your idea to everyday use.
Product design and full-stack engineering for AI applications, multi-step agent systems and software products that need dedicated design and evaluation.
On this page
Who it helps
- Founders building an AI-first product who need a design and engineering team rather than a prototype.
- Established businesses productising an internal capability for customers or partners.
- Teams with an existing product that needs AI features built properly rather than bolted on.
Problems it addresses
You have a validated idea or an internal process worth turning into a product, but it needs real engineering: data, evaluation, interface, billing and operations.
- A demo that impressed everyone but cannot be measured or scaled.
- AI features that feel like a chat box glued onto the side of an app.
- No way to know whether a model change made the product better or worse.
- Unclear costs per user because model usage was never designed in.
- A prototype built by one person that nobody else can maintain.
What the engagement includes
An application with language-model capability at its core, built with an evaluation harness from the start so quality can be measured, plus the ordinary parts a product needs: auth, billing, admin and monitoring.
- Product discovery and scoping: the one workflow users will pay for first.
- Interface and interaction design for AI features, including uncertainty and correction states.
- Application engineering: web app, API, data model, auth, billing and admin.
- Agent and retrieval design with an evaluation set built from real examples.
- Deployment, observability, cost tracking and a security review before launch.
- Handover of repositories, infrastructure and documentation to your team.
A concrete example
A product you can put in front of users, measure honestly, and keep improving. Code, prompts, data and infrastructure are yours.
Illustrative scenario: document review assistant for a professional services firm
Illustrative- ScopeReviewers upload client documents, get a structured summary with flagged clauses, and correct anything wrong. Corrections feed the evaluation set.
- BuildWeb app with role-based access, document pipeline, retrieval over the firm’s own precedents, review interface with side-by-side citations.
- MeasurePrecision and recall of flagged clauses against a reviewer-labelled set, time per review, and cost per document.
- ShipPilot with a small group, weekly demos, then wider rollout once quality targets are met.
Illustrative scope written to show how a product engagement is structured. Not a description of a delivered client project.
Supported integrations
Anything with an API is a candidate. These are the ones we work with most; if your tool is not listed, ask, and we will confirm before you commit.
- Claude, GPT-class and open-weight models, chosen per task
- Postgres, vector search and document pipelines
- Stripe for billing and usage metering
- Auth providers such as Clerk, Auth0 and Supabase
- AWS, Google Cloud, Vercel and your own infrastructure
- Existing products via API
Delivery expectations and cost drivers
Product work runs in short cycles with a working demo each week. A first usable version for pilot users is the usual first milestone; the timeline to get there depends on the scope you choose to launch with.
What drives the price
- Breadth of the first release, and how much can wait until after launch.
- Data availability and quality for retrieval and evaluation.
- Design complexity and number of user roles.
- Compliance, security and hosting requirements.
Ongoing costs after launch
Ongoing costs are cloud hosting, model usage, and third-party services such as payments and email. We design cost tracking into the product so you can see cost per user from day one.
Ongoing support
After launch we can continue as your product engineering team, hand over to your own engineers with a structured transition, or support them on a retainer.
Questions about Custom AI Products
Which models do you build on?
We are model-agnostic. Models are chosen per task for quality, latency and cost, and the product is built so the model can be swapped when a better one arrives.
Can you work with our existing engineering team?
Yes. We can lead the AI parts while your team owns the rest, or embed alongside them. Repositories, standards and reviews are shared from the start.
Who owns the code, prompts and data?
You do. Deliverables are assigned to you on payment as set out in the engagement agreement, and everything runs in accounts in your name.
Related
AI Reception & Lead Handling
Voice and WhatsApp agents that pick up enquiries in seconds, ask the qualifying questions your team would, book appointments into the calendar and hand off to a person when it matters.
Workflow Automation & Integrations
Connected workflows across CRMs, calendars, support desks, documents and internal tools, with clear rules for approvals and exceptions.
Next step
Talk to us about Custom AI Products.
Tell us what you are dealing with. We reply by email to arrange a short call, then send a written scope and price before any work starts.