#01
New AI product idea
You see a business opportunity in AI — for example, an intelligent tool built on your own data — but you can't build it alone. You need a team that ships real products, not just prototypes.
SERVICE
AI product & platform development
A new AI-based product or internal tool, from concept to launch.
Let's talk about your projectWe'll reply within a few days with a concrete proposal.
What we deliver
What this looks like in practice.
We build new AI-based products: customer-facing platforms, internal tools, or SaaS. We validate the concept with market and user feedback, then deliver a production-ready system — backend, web, mobile where needed. From the first sketch to live deployment, one team end-to-end.
Validation & concept
Workshop with your team, target-market definition, technical feasibility and ROI estimate.
AI architecture design
Model selection (LLM, RAG, fine-tuning), agent design, evaluation strategy.
MVP in 2–4 week sprints
A working prototype tested with real users, with continuous demos.
Production-ready system
Scalable backend, web and mobile, observability and security built in.
Launch readiness
Deploy process, security review, performance and load testing.
Continuous iteration
Weekly metric reports, model refinement, A/B tests based on real usage.
When you need this
This is where we come in.
#02
AI-powered internal tool
You have a process that takes long and involves a lot of manual work (document processing, quote generation, customer communication), and you know AI could speed it up. You want an internal tool that makes your team's daily work easier.
#03
AI-first SaaS product
You're bringing a SaaS product to market where AI is the core value — not an added feature, but the centrepiece. You know that initial architecture decisions will shape development for years.
A concrete example
What an engagement looks like in practice.
Anonymised, illustrative project example.
Starting point
A European fintech wanted to reduce the time their KYC team spent on manual document review — without losing accuracy.
Weeks 1–2
Validation
Workshop with the KYC team, AI model selection (LLM + OCR), PoC scoping. Measurable hypothesis: significant reduction in manual hours.
Weeks 3–6
MVP
Closed prototype on real customer documents. Node.js backend, AI pipeline, simple admin UI for human verification.
Weeks 7–10
Production
Integrated into the existing KYC system via API. Auth, audit log, security review, fallback workflow for edge cases.
Weeks 11+
Iteration
Weekly reports after launch — accuracy, manual override rate, cost. Model refinement based on real usage.
Outcome
After ten weeks, a significant portion of manual KYC work is automated; freed capacity focuses on complex cases.
Related services
Often these go together — adjacent services we also handle.
FAQ
Common questions
How long does a typical AI product build take?
From validation to launch typically 10–16 weeks. Depends on scope, but we work in 2–4 week sprints so you see progress continuously.
Who works on the project?
As founder, I'm personally on every project. Depending on scope, I bring in senior specialists from my network (AI engineer, UI/UX, DevOps) — you meet them up front.
What if the validation phase says the idea won't work?
That's a successful outcome. Validating that an AI product idea has no ROI saves you 3–6 months of building the wrong thing.
What happens after launch?
We continue operating and iterating — the build + run model. Same team, no handover to a separate ops crew.
Get in touch
Have a project in mind?
Let's talk about it. We'll reply within a few days, and a 30-minute call will tell us whether we're a fit.
Send an Email
Write us about your project. We'll reply within a few days.
Get in touchCall Us Now
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