AI-native products
RAG, agents, generation, recommendations and workflow features designed around a real user need.
AI SaaS Development
Turn your AI SaaS idea into a production-ready product
From product specification and UX to AI architecture, billing, deployment and analytics—one senior team owns the path to launch.
Founder-friendly discovery
Production architecture
Post-launch support
Business problems
Move from idea or prototype to a product people can use
SaaS foundations
Authentication, roles, multi-tenancy, billing, admin tools and analytics that do not need rebuilding after launch.
Launch readiness
Secure deployment, monitoring, usage controls and a product iteration loop for the first customers.
Example workflows
See what the future process looks like
Each engagement is designed around the systems and approval points your team already uses.
Product discovery
1Define user and problem
2Prioritise the MVP
3Map AI risks
4Prototype the workflow
5Agree launch metric
Product build
1Architecture
2UX and UI
3AI and application build
4Weekly demos
5Security and testing
Launch and learn
1Production deployment
2Analytics
3User onboarding
4Monitor AI usage
5Plan next iteration
What is included
A complete path to production
Start with the smallest engagement that can prove value. Expand after the evidence is clear.
Product discovery
Technical architecture
UX/UI
AI and RAG integration
Agent workflows
Frontend and backend
Authentication and roles
Multi-tenancy
Billing
Deployment and monitoring
Delivery model
Pilot, prove, then scale
Discover
Turn the idea into a product specification and measurable MVP.
Prototype
Validate the riskiest user and AI interactions before the full build.
Build
Ship the product in visible increments with regular demos.
Launch & iterate
Deploy, measure usage and improve with real customer evidence.
Investment guidance
Know the likely range before the call
These are positioning ranges, not quotes. Data readiness, integrations, security and scope determine the final proposal.
Product discovery
$1,000–$3,000
Scope, workflow, architecture and delivery plan.
Prototype
$3,000–$7,500
Validate the product experience and technical risk.
AI SaaS MVP
$15,000–$35,000
Production-ready first release for real users.
Ongoing engineering
$3,000+/month
Post-launch delivery, monitoring and product growth.
Questions
Straight answers before we scope
Can you work with an existing prototype?
Yes. We audit what is reusable, identify production gaps and propose the smallest safe path forward.
Who owns the source code?
The client owns the agreed code and deliverables, with work kept in accessible repositories and documented for handover.
Which AI providers do you support?
Provider choice depends on product needs, data sensitivity, latency and cost. We design the application so the provider is a controlled dependency rather than the whole product.
Do you provide post-launch support?
Yes. We can hand over after launch or continue as the product engineering team.
A practical first step
Ready to automate your business or launch an AI product?
Tell us which process is consuming time or what product you want to launch. We'll recommend a focused first step.