The AI-nativeteam isn't bigger.
It's smarter.
For decades, building software meant hiring seven specialists and watching projects slow down as the team grew. We build differently: you bring the idea, we do the rest — we train AI on your business, and one integrated AI-powered team takes it from idea to launch to growth. Weeks, not months.
Built around AI — not just using it.
Our take
Today's best development teams don't simply use AI — they're built around it. The industry has a name for this: AI-native development— teams and methods designed around AI from day one, not retrofitted onto it. It's how we've worked from the start. Every engagement begins the same way: we train AI on your idea and your business — your market, your customers, your constraints — so every role that touches the product already understands it. AI handles the research, drafting, coding, testing and automation. Our people handle strategy, architecture, security and judgement. That's what makes it faster, cheaper — and far more effective.
- What you bring
- The idea and what you know about your business. That's genuinely all we need to start.
- What we train
- AI, on your business — market, competitors, customers — before a single screen is designed.
- Who engineers
- Humans. Architecture, security, scalability and real business problems stay with our engineers.
- What it replaces
- Not people — unnecessary complexity. No coordinating five agencies and a freelancer roster.
- Project managerSalary + ramp-up
- UI/UX designerSalary + ramp-up
- Frontend developerSalary + ramp-up
- Backend developerSalary + ramp-up
- QA engineerSalary + ramp-up
- DevOps engineerSalary + ramp-up
- Technical writerSalary + ramp-up
Projects got slower as teams got larger — more handoffs, more meetings, more waiting.
- The VisionaryFind the opportunity
- The PrototyperBring the idea to life
- The BuilderShip production software
- The SweeperImprove after launch
- The GrowerAcquire users & revenue
- The Health TeamKeep it future-ready
The team expands and contracts around your project — expertise without the overhead. Instead of “who do we hire?”, we ask “what does the product need next?”
Train. Prototype. Build. Grow.
The same loop for a custom app, a web platform or a mobile product — in any industry. The difference from a traditional agency is what happens first: the AI learns your business before anyone opens a design tool.
Custom, web, mobile — every industry.
Customer apps for retail, health, finance, logistics, education, real estate — the method doesn't care about the industry, because the AI is trained on yours before we start.
Bespoke software shaped to one business's exact workflow — internal tools, portals, platforms nobody sells off the shelf.
Full-stack web platforms — SaaS, dashboards, customer portals — built AI-first on Next.js, NestJS and Python.
iOS and Android customer apps — prototyped in days, engineered for the store review and the years after it.
RAG, agents, classifiers and chat built into the product — across OpenAI, Anthropic, Gemini and local models.
Interactive prototypes and minimum viable products stakeholders can test before committing real budget.
Storefronts and the systems behind them — where our AI build method meets our ecommerce development practice.
Small custom features and mini apps for normal websites — the solutions that used to be too expensive to build.
Not every solution is a big build.
Historically, custom software meant a big project — for anything small you bought a plugin, settled for off-the-shelf, or let the idea go. Building a small standalone tool for one business was simply too expensive. AI changed that economics.
A colour & finish configurator on a Shopify product page: the visitor picks a shade, and a Gemini-rendered preview appears on the fly. A feature no plugin sells — built as a micro-build, not a platform.
A clinic website wired straight into the existing appointment system — a small, precise integration that would once have been quoted as a project of its own.
A calculator on a service page. Data pulled from your channels and auto-published to your site. A quiz that qualifies leads. Ordinary websites can now afford custom features — at a fraction of the old cost.
We call these Micro-Builds — small custom features and mini apps that help your business and your customers, without committing to a huge platform. Every size of business qualifies.
One team. Six AI specialists.
Every modern product needs the same six roles. Traditional teams staff them with headcount; we staff them with AI-powered specialists that switch on when your product needs them.
The pipeline is a loop, not a line. What the Sweeper learns feeds the Grower; what the Grower learns feeds the next Visionary cycle. One integrated team, from the first conversation to long after launch.
Proof, not promises.
Builds where AI did real work inside the product — including Zento, our own platform: proof we trust this method enough to run our own software on it.
A recruiter's website with an AI application engine inside.
A WordPress site for a German recruitment agency with a custom, AI-based candidate application system embedded into it — built in Python to screen and route applicants from the page itself.
Our own product — offline sales, tracked back to the ad.
Zento is software we built and run ourselves: a CRM-connected tracking platform that passes completed real-world sales back to Google and Meta like site conversions — so ad budgets learn from the truth, not just clicks. Live at zentodash.com, maintained by the same team that built it.
We've shipped across six sectors.
Different categories, same playbook — build, grow, automate. A sample of the brands in each.
The stack we choose from.
There's no single winning AI stack yet — so we keep ours intentionally lean: a small set of tools that cover the whole lifecycle and complement each other, instead of dozens of disconnected apps. One tool per role, matched to the project.
- Claude · ChatGPT · Gemini
- Perplexity (deep research)
- NotebookLM · Notion AI
- Figma + AI
- Lovable · v0
- Bolt.new
- Claude Code (agentic)
- Google Antigravity
- Cursor · GitHub Copilot
- Windsurf · Replit
- PostHog · GA4
- Microsoft Clarity · Hotjar
- Optimizely
- Semrush · Ahrefs
- Midjourney · Runway
- Higgsfield · Remotion
- n8n (automation)
- Vercel · AWS
- Supabase · Cloudflare
- Sentry · GitHub Actions
We build in stacks the AI tools speak natively — which is exactly why we build in them: faster to ship, cheaper to run, easier to maintain. The exact set is chosen per project, to serve the product — never the other way round.
AI doesn't replace people.
It replaces unnecessary complexity. Less management, less waiting, less overhead — more building, more improving, more growing. These are the rules that keep it honest.
- AI accelerates, humans engineer
- AI drafts, codes and tests; our people own strategy, architecture, security and decisions. Never the reverse.
- Roles, not headcount
- The team is built around what the product needs next — it expands and contracts with the project.
- See it before you fund it
- Nothing expensive gets built before a clickable prototype has been tested by real stakeholders.
- You own the result
- Your code, your infrastructure, your data. AI-assisted doesn't mean black box — everything is documented and handed over.
- Launch is the start
- Improvement, growth and health checks are part of the product, not an upsell after it.
- Honesty is the edge
- No inflated velocity claims, no “AI magic”. We'll tell you what AI genuinely speeds up — and what still takes engineering time.
Start small. Scale when it's proven.
Each step de-risks the next: nothing gets built before it's validated, nothing gets funded before you've clicked it. Every sprint's output is yours to keep — whoever builds next.
- AI trained on your idea & business
- Market & competitor research
- User personas & feature plan
- Technical architecture
- Honest build / don't-build verdict
- Wireframes & UX flows
- Interactive clickable prototype
- Stakeholder & user testing
- Scoped MVP plan
Creditable toward the build.
See it first →- Full-stack development — web, mobile or custom
- AI integrations where they earn their place
- Architecture, security & scalability by our engineers
- Documentation & testing throughout
- Deployment on Vercel or AWS
- Launch — with your code, your infrastructure, your data
Scoped from the Discovery and Prototype sprints — so the quote is based on a validated plan, not a guess.
Start the build →- Continuous optimisation & bug fixes
- Security updates, backups, monitoring
- Performance & infrastructure care
- Growth: SEO, content, ads, CRO
The build doesn't work alone.
AI development sits inside the same loop as design, ecommerce and growth — the services the six roles lean on most.
You bring the idea. We do the rest.
Tell us what you want to build — an app, a platform, a product. We'll train the AI on your idea and come back with what we'd validate, prototype and ship first. The first reply comes from a partner, not a form.