AI Prototyping
Enablement.
Your team. Your repo. Your stack. Fully self-sufficient in 3 weeks.
We design a secure sandbox architecture, build a pilot prototype side-by-side with your team, and leave them with the skills, tooling and confidence to ship AI prototypes independently. No black boxes. No vendor lock-in. No 6-month timelines.
If any of this is you — we built this service for you.
"We have an AI strategy but no prototypes."
Strategy without shipping is slideware. We get your team from zero to a live prototype with real users in 3 weeks — so the strategy has evidence.
"Our prototyping team is stuck waiting for infra."
We build a sandbox that is completely decoupled from your core systems. No infra tickets, no architecture review boards, no 6-week procurement cycles. Your team ships on day one of week two.
"We hired smart engineers but they have never built with LLMs."
We pair-program with your team on a real prototype. Not a workshop. Not a slide deck. Hands on keyboards, explaining every decision in context. After 3 weeks they do not need us.
"We need to test AI ideas on real customers — safely."
The sandbox runs on fake or anonymised data, has no write access to production systems, and makes no real business decisions. Your compliance team signs off because the guardrails are built in from day one.
"We tried a vendor prototype but nobody on our team can maintain it."
We do not hand over a black box. We build it with your team, in your repo, on your stack. When we leave, they own every line. That is the point.
"We do not know which stack to use."
We recommend proven, simple, cheap tools: Next.js or React for the frontend, Supabase or Firebase for the backend, Vercel or Cloudflare Pages for hosting. Opinionated choices — because choosing a stack should take an hour, not a quarter.
3 weeks. Architecture → prototype → enabled team.
Three focused weeks. At the end your team builds prototypes without us. That is the only success criterion that matters.
Architecture + environment setup
- Sandbox architecture design: frontend (React / Next.js), backend (Supabase / Firebase), hosting (Vercel / Cloudflare Pages), mock APIs — fully decoupled from your core systems
- Security & compliance guardrails: fake / anonymised data policy, read-only integrations, no real decisioning (e.g. no live credit approvals), GDPR-safe testing flows
- Environment provisioned and ready-to-use: CI/CD pipeline, staging + preview URLs, secrets management, monitoring
- Starter template committed to your repo: authenticated shell, design-system basics, API scaffolding, deployment script — your team clones it and has a running prototype in < 10 minutes
Pilot prototype + hands-on pairing
- Pick a real use case together (onboarding flow, SME lead qualification, product recommendation, internal tool — whatever delivers the most learning)
- Build the pilot prototype side-by-side with your team — pair programming, not handoff. Every architectural decision is explained live, in context.
- Integrate AI capabilities: Claude / GPT endpoint wiring, prompt design, evaluation, fallback handling, streaming UX
- Deploy to preview environment, connect test users, instrument basic analytics
Handover + team enablement
- Your team builds a second prototype independently — we coach, review and unblock, but they drive
- Tooling deep-dive: Claude Code, Cursor, prompt iteration workflow, evaluation harness basics, rapid A/B testing patterns
- Documentation handover: architecture decision record, deployment runbook, data safety checklist, prototype template guide
- Final review: success criteria check, knowledge gaps addressed, ongoing support model agreed
What the sandbox architecture looks like.
Frontend
React or Next.js (your preference or ours). Server components for speed, client components for interactivity. Streaming AI responses via server-sent events. Tailwind for styling. Deployed to Vercel or Cloudflare Pages with instant preview URLs per branch.
Backend + data
Supabase (Postgres + auth + storage + real-time) or Firebase (Firestore + auth + storage). Read-only mock APIs where integration with production systems is needed. No direct access to core databases — ever.
AI integration
Anthropic Claude or OpenAI GPT via API. Prompt design, evaluation harness, streaming UX, fallback handling, cost monitoring. Server-side proxy so API keys never touch the browser. Optionally RAG (retrieval) over product catalogues or internal docs.
Security & compliance
Fully isolated from production: separate cloud project, separate auth, separate data. Fake or anonymised test data. No real business decisions (no credit approvals, no underwriting, no KYC). PII stripped before LLM processing. Your DPO and compliance team review the guardrails before week 2 begins.
CI/CD & DevOps
GitHub Actions or Vercel auto-deploy. Preview URL per pull request. Secrets in environment variables (not hardcoded). One-click rollback. Your team pushes → prototype is live in 90 seconds. No infra tickets.
Tooling & workflow
Claude Code, Cursor, or VS Code + Copilot — we train your team on whichever AI-assisted development tool fits their workflow. Prompt iteration patterns. Evaluation-driven development. How to go from idea to deployed prototype in a single afternoon.
What you walk away with.
Sandbox architecture
Documented, deployed, decoupled from core. Frontend + backend + hosting + CI/CD + secrets.
Security & compliance guardrails
Data handling policy, anonymisation strategy, no-real-decisioning rules, GDPR-safe testing patterns.
Ready-to-use environment
Your team opens a laptop and starts building. No setup ritual, no waiting for infra tickets.
Starter template
Clone → build → deploy in < 10 minutes. Authenticated shell, API scaffold, design-system basics, deploy script.
1 live pilot prototype
Real use case, real users, deployed and instrumented. Built together with your team, not handed over as a black box.
Enabled team
Your 3–4 people can independently design, build, deploy and test an AI prototype within 2–4 weeks. No external dependency.
Concise documentation
Architecture, deployment, data safety, tooling — written for engineers, not for auditors. Short, actionable, maintained in your repo.
How we know it worked.
We do not measure success by deliverables shipped or hours billed. We measure it by one thing: can your team build the next prototype without us?
Your team independently builds a new prototype in 2–4 weeks (without us)
The sandbox is secure and fully isolated from production
At least 1 prototype is live and tested with real users
The team understands the stack, the tooling and the workflow — and can explain it to a newcomer
We do not just consult. We build — and we teach.
Engineers who ship
Your team pairs with people who have shipped production AI systems — not with junior consultants reading from a playbook. Every decision is grounded in real-world experience.
Academic R&D meets commercial pragmatism
Skygena combines a Ph.D.-led research bench with two decades of enterprise transformation experience. We know what works in a lab AND what survives contact with production.
No vendor lock-in
Everything we build is in your repo, on your cloud, using open-source or commodity tools. When we leave, there is no proprietary platform to pay for.
Governance from day one
The sandbox is designed for compliance review — isolated, auditable, no-real-decisioning. Your DPO and risk team are briefed before the first line of code is written.
Ready to give your team AI superpowers?
30-minute scoping call with a founder. We will tell you honestly whether this engagement fits your team, your timeline and your constraints — and what the first week would look like.