AI products people actually use
We design and build AI-first MVPs and add AI features to existing products. Discovery, interfaces that let users check and correct AI output, quality testing and running costs are part of the build, not an afterthought.
Demo-ware is easy. Products are hard.
of organizations say AI is already growing their revenue, while 74% hope it will. The gap is between a working demo and a product people rely on.
Source: Deloitte, State of AI in the Enterprise, 2026
What goes wrong
- A thin wrapper around a model with no lasting advantage
- Interfaces that assume the AI is always right
- No evaluations, so quality drops silently after launch
- Token costs that grow faster than revenue
What we do instead
- Build the advantage into workflows and proprietary data
- Design for uncertainty: citations, confidence, easy correction
- Ship with automated evaluations and monitoring
- Model unit economics before launch, not after
Who it's for
Founders
You need a credible AI product and a defensible story for investors, without burning the round.
Product managers
You need AI features users adopt, with quality you can measure release to release.
Enterprise innovation teams
You need a new AI product built to production standards your IT team will accept.
How it works
Typical timeframe: 6‑12 weeks. Every engagement is scoped to your situation after the discovery call.
Discovery and design
We confirm the user problem, design the experience around imperfect AI output, and choose the architecture and models.
- User flows and prototypes
- Architecture and model choice
- Evaluation plan
Build in short cycles
We build in weekly increments you can click through, with evaluations running on every change so quality never drifts.
- Working weekly releases
- Automated evaluation suite
- Integrations with your systems
Launch and learn
We launch to real users, instrument usage and quality, and hand over a product your team can run and extend.
- Production launch
- Monitoring and cost dashboards
- Documentation and handover
You leave with
- A launched product or feature with real users
- Full ownership of code, prompts and evaluation sets
- Dashboards for quality, usage and cost per task
- A team that knows how to extend it
How we build
- Model-neutral architecture, so you can switch providers
- EU hosting and data residency where needed
- Transparency and disclosure built in for the EU AI Act
- Security and privacy reviewed before launch
- Joint builds with your engineers, so the knowledge stays in-house
Our founder co-founded VantageKit, an AI deal-intelligence platform that reached 100+ business customers in its first year with no sales team. Earlier, at Bonial (Axel Springer), he led the ML personalization that lifted conversion 1.8x for an app with 2M monthly active users.
See case studiesCommon questions
Is my product just a wrapper around a model?
It is if the only thing you own is a prompt. We help you build advantage that a model update cannot copy: proprietary data, deep workflow integration and an experience tuned to your users.
Which models and stack do you use?
Whatever fits. We work with commercial and open models and pick per task based on accuracy, cost, latency and data residency. The architecture lets you change models later without a rewrite.
How do you keep AI quality from drifting?
Every product ships with an evaluation suite built from real examples. It runs on every change and in production, so you see quality move before your users do.
Who owns the code and IP?
You do. Code, prompts, evaluation sets and documentation are yours, with no license fees or lock-in. Ownership terms are set out in our contract.
Can you work with our in-house team?
Yes. Many builds are joint, with your engineers pairing with ours so the knowledge stays when we leave.
Related services
AI Strategy & Opportunity Mapping
Rank your AI opportunities by value and feasibility, check data readiness, and decide what to build, buy, or skip in 1‑2 weeks.
AI Validation Sprints
A working AI prototype on your real data in 2‑4 weeks, with evaluations, cost per task and a clear go or no‑go decision.
AI Agents & Automation
AI agents for well-defined workflows, running in your systems, with human escalation, audit trails and measured savings.
AI Governance & Enablement
Proportionate AI governance for the EU AI Act and GDPR, plus hands-on AI training for your team on the tools they actually use.
Build the AI product your users will keep using
Book a 30-minute call to talk through your product idea or feature. We will share how we would approach it and what to validate first.