MVP build
From concept to launched product. Spec, design, build, deploy. Enterprise AI models in the workflow from day one.
- From £15,000
- 8 to 14 week build
- Hosting and CI/CD included
Services
Software built with enterprise AI, not shortcuts.
Spec-driven platforms and SaaS products, built with Claude and Copilot under proper engineering discipline. CI/CD, security scanning, and a team that stays after launch.
Why build with Netix
AI accelerates. Engineers decide.
Most agencies use consumer AI tools to cut corners. We embed enterprise models (Claude, Copilot) into a disciplined development workflow: written specs, code review on every line, automated security scanning, and CI/CD from commit one.
You get software that ships faster without the quality trade-off. Every feature is specced before it is built, tested before it ships, and monitored after it launches.
How we build See what we have built
Enterprise AI inside a proper engineering workflow.
AI writes the first draft. Engineers review, test, and ship. Every commit is scanned, every feature is specced, every deploy is automated.
Build
- Written spec before every feature
- Enterprise Claude and Copilot models
- Code review on every line, AI or human
- Automated test suites from day one
Ship
- CI/CD pipeline from first commit
- SAST and dependency scanning in CI
- Staging mirrors production exactly
- Go-live checklist, no surprises
Pipeline green CI
Build passed. SAST clean. 0 vulnerabilities. Dependency audit clear. Ready to deploy.
Security scan results, last 10 deploys
0 / critical
Process
Six steps. No ambiguity.
Every engagement follows the same rails. AI accelerates the build, not the corners.
- 01
Discovery and scoping
Requirements workshop, technical feasibility, architecture decision record. Scope locked before a line of code.
- 02
Spec-driven design
Written specification before implementation. Figma for UI, data model diagrams, API contract definitions. Approved before build.
- 03
AI-assisted build
Enterprise Claude and Copilot models embedded in the development workflow. Every line reviewed. AI accelerates, engineers decide.
- 04
CI/CD and security scanning
Automated pipeline from commit one. Dependency scanning, SAST, container scanning. Vulnerabilities caught before they ship.
- 05
UAT and launch
Staging environment mirrors production. User acceptance testing, performance benchmarks, go-live checklist. No surprises.
- 06
Ongoing evolution
Retainer sprints, feature requests, monitoring, dependency updates. The codebase stays healthy after launch.
Three paths
Pick the engagement that fits.
Every engagement begins with a free discovery call so you can pressure-test the recommendation.
Platform extension
Add features, integrations, or rebuild a subsystem on an existing product. Scoped, specced, delivered.
- From £5,000
- Scoped per engagement
- Security review included
Retained development
Ongoing monthly sprints. Dedicated capacity, shared backlog, CI/CD maintained. The team that built it keeps it healthy.
- From £3,500/mo
- Dedicated capacity
- Monthly reporting
Table stakes
Everything below is included. Every time.
We do not charge extra for the practices that should never have been optional.
Spec-driven development
Every feature starts as a written spec. No ambiguity, no scope creep, no "that is not what I meant."
- Written and agreed before we build
- No ambiguity, no scope creep
- You approve the plan, not a surprise
Enterprise AI models
Claude, Copilot, and internal tooling. Not consumer chatbots. Models that understand codebases, not just prompts.
- Models with proper data handling
- Your data is not training anyone
- Governed access, logged usage
Security scanning
SAST, dependency audit, container scanning. Baked into CI, not bolted on after launch.
- SAST and dependency audit every push
- Container scanning before release
- Build fails rather than ships a hole
Automated testing
Unit, integration, and end-to-end tests. Coverage targets agreed at scoping. Regressions caught before deploy.
- Unit, integration and end-to-end
- Targets set before we start
- Regressions caught by machines
Monitoring and observability
Logging, error tracking, uptime monitoring from day one. You know what your platform is doing.
- Logging and error tracking from launch
- Uptime monitored externally
- You hear it from us first
Ongoing retainers
Monthly sprints, bug fixes, feature work. The team that built it maintains it.
- Monthly sprints, not ad-hoc chaos
- Bug fixes and feature work together
- No handover to strangers
Free · no slide deck
Have a platform in mind?
30 minutes with a developer and an architect. We will look at what you need, what is realistic, and give you a rough budget and timeline before you commit to anything.