Rapid prototypes
Turn a raw idea into an interactive or functional prototype you can put in front of users, stakeholders, or investors.
AI-native product development
Ambitious ideas, built
into working products.
An AI-native development studio building rapid prototypes, MVPs, applications, and intelligent agents. One compact product team from first call to deployment, building software real users can rely on, not something that only looks good in a demo.
Delivery time follows scope: prototype sprint to full build
Clear scope. Weekly builds. Source code included.
Built with the tools modern products run on
What we build
From the first prototype to the version your users depend on.
One team covers product thinking, design, engineering, and AI implementation. Start with proof, move to a launchable product, and keep shipping from there.
Launchable MVPs
The smallest complete product that can onboard real users, collect feedback, and test the business assumption behind the idea.
AI-powered applications
Web and mobile products with language models, intelligent search, recommendations, generation, or decision support built into the experience.
AI agents and automation
Agents that use tools, retrieve data, follow a defined workflow, request approval where it matters, and complete real business tasks.
Full product development
Customer-facing SaaS platforms, marketplaces, portals, internal tools, and mobile applications, designed and built end to end.
MVP rescue and scale
Take over a partially built or AI-generated product, repair the architecture, improve the UX, add security, and prepare it for real usage.
How it works
Four steps from idea to real users.
One owner, a written scope, weekly demos, and code that belongs to you. No black-box delivery and no month of silence between updates.
Discovery
Understand the user, the business objective, and the workflows that matter, then agree the smallest credible scope in writing.
Prototype
Map the journey and build the core interface as something clickable, settling the important product decisions before deep development.
Build
Working software every week, reviewed in a short demo and tested against real workflows, edge cases, permissions, and AI behaviour.
Launch
Deploy, watch how people actually use it, remove friction, and prioritise the next version from real feedback.
Ways to build
Choose the build that matches your stage.
Some founders need proof that the idea works. Some need a first product real users can sign into. Some need a product team that keeps shipping. Scope decides the timeline, and we agree it in writing before work starts.
Featured
Prototype sprint
A short, tightly scoped sprint that turns the idea into something people can click through and react to. We map the core flows, design the key screens, and build a working prototype, including the AI workflow if the product depends on one.
Outcome: a testable product and a costed plan for the MVP
Book a build call
Prototype sprint
In review
Core flows mapped
7
Onboarding
AI review
Billing
Core screens built
AI workflow wired
Assumption to test: pricing
Feedback items open: 9
Screens
14
Test sessions
6
Build readiness
82%
Illustrative interface. Every sprint ends with a working prototype and a written build plan.
MVP build
A complete first product, built end-to-end and deployed. Timeline follows the agreed scope.
Product scopingUX and UI design
Frontend and backendAuthentication
DatabaseAI and API integrations
Payments when neededDeployment
AnalyticsSource-code handover
Product partner
An ongoing product team once the first version is live and the roadmap keeps moving.
Product designWeekly shipping
New featuresTechnical maintenance
AI experimentationPerformance work
ReliabilityRoadmap support
AI capabilities
AI that does useful work inside the product.
We add AI where it changes the outcome for the user, not as a feature label. Every capability below ships with limits, logging, and a human in the loop where the decision matters.
Agents and tool use
Agents that call your systems, follow a defined process, and stop for approval on anything sensitive.
RAG and private knowledge search
Answers drawn from your own documents and data, with sources attached so people can check them.
Document processing and extraction
Turn PDFs, forms, and messy files into structured records your product can act on.
Voice and multimodal interfaces
Voice agents, image and audio input, and natural-language controls where typing is the wrong interface.
Recommendation and scoring
Ranking, matching, and prioritisation that help users decide what to do next.
Workflow automation
Repeated steps handled automatically, with escalation rules and an audit trail behind them.
Evaluation and observability
Test sets, quality checks, and monitoring so you can see how AI features behave in production.
Model integration
OpenAI, Anthropic, Gemini, and open-source models, chosen per task on cost, quality, and privacy.
MVP rescue
Your prototype worked. Now make it launchable.
Getting a first version out of an AI builder is a real result. It proved the idea was worth building. The next step is different work: structure, security, and reliability so real users can depend on it. We take over products started with Lovable, Bolt, Replit, Base44, Bubble, FlutterFlow, Cursor, Claude Code, other contractors, or an internal team.
We start with a codebase audit and tell you plainly what is worth keeping, what needs rebuilding, and what it takes to get to production.
Request an MVP rescue auditTypical rescue work
Codebase auditArchitecture repair
Database restructuringAuth and permissions
API reliabilityResponsive UI fixes
Security hardeningDeployment setup
MonitoringPerformance
Test coverageProduction readiness
Selected builds
The kinds of products we build.
Concept builds and internal products, labelled honestly. Client work is shown only where we have permission to share it.
B2B SaaS
Concept build
AI lead intelligence platform
Problem. Sales teams sit on inbound leads with no idea which ones deserve attention first.
Built. Enrichment pipeline, scoring model, and a review queue where reps confirm or override every ranking.
Next.js
Postgres
Scoring
View the detail
Consumer
Demonstration
Career navigation assistant
Problem. People changing career have plenty of advice and no clear next step.
Built. Guided intake, skills mapping against real role requirements, and a plan the user can edit and track.
React
RAG
Supabase
View the detail
Customer portal
Concept build
AI-enabled customer portal
Problem. Support answers the same account questions dozens of times a week.
Built. Self-serve portal with document search over the customer's own records and a clean handoff to a human.
Next.js
Retrieval
Auth
View the detail
Multi-agent
Internal product
Multi-agent outreach workspace
Problem. Research, drafting, and follow-up live in five tools and nothing stays in sync.
Built. Agents that research and draft, with a single approval inbox before anything is sent.
Python
LangGraph
Approvals
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Internal tools
Internal product
Internal operations automation
Problem. Order and invoice handling done by hand across spreadsheets and email.
Built. Extraction from incoming documents, matching rules, and an exception queue for anything uncertain.
Python
Extraction
n8n
View the detail
Vertical SaaS
Concept build
Vertical SaaS MVP
Problem. A niche industry running on shared spreadsheets and WhatsApp threads.
Built. Onboarding, the one workflow the business runs on, billing, and an admin view, the smallest launchable version.
Next.js
Stripe
Supabase
View the detail
Questions
Answers before the first call.
How quickly can you build an MVP?
It depends on scope, and we will tell you the honest range on the first call. A prototype sprint is short by design. A launchable MVP takes longer because it includes auth, data, payments where relevant, and deployment. We would rather agree a realistic plan than quote a headline number we cannot keep.
What happens during the first call?
We go through the user, the core workflow, what the first version should include, the risks, and the likely delivery path. You leave with a clear view of the next step, whether or not you build with us.
Can you help define the product scope?
Yes, most engagements start there. We help you cut to the smallest version capable of proving the idea, and write down what is in, what is out, and what comes next.
Do you handle both design and development?
Yes. Product thinking, UX and UI design, frontend, backend, AI implementation, and deployment sit with one team, so nothing is lost in handover.
Can you add AI to an existing application?
Yes. We review the current product and data, then add AI where it creates real value for the user: search over your own content, drafting, extraction, scoring, or an assistant inside an existing workflow.
Can you take over a Lovable, Bolt, Replit, or Bubble project?
Often, yes. We start with an audit and tell you what is reusable and what should be rebuilt. Sometimes the fastest route to production keeps most of the existing work; sometimes it does not. Either way you get the reasoning, not just a quote.
Will I own the source code?
Yes. The code lives in your repository from the start, in your accounts and infrastructure, with documentation for handover.
What happens after launch?
You can take it in-house, keep us on a defined support arrangement, or continue as a product partner with weekly shipping. There is no lock-in either way.
How do you keep AI features from behaving unpredictably?
Narrow scope, structured outputs, validation before anything is written or sent, test sets for the cases that matter, human approval on sensitive actions, and logging so behaviour can be inspected after the fact.
Do you sign NDAs?
Yes, before the first detailed conversation if you prefer. Send yours or use ours.
What technologies do you use?
Typically React and Next.js on the front end, Node or Python services, PostgreSQL or Supabase for data, Stripe for payments, and OpenAI, Anthropic, Gemini, or open-source models for AI. We choose per project rather than forcing one stack.
Can you work with our existing product team?
Yes. We can own a defined slice of the roadmap, work alongside your engineers in your repository and rituals, or lead delivery while your team stays on core product.
Your idea does not need another month in a document.
Bring an idea, a half-finished prototype, a product brief, or a business problem. We will tell you what the first version should be and what it takes to build it.
On the first call we will discuss the user, the core workflow, the right first version, the risks, and the likely delivery path.