Artificial intelligence integration
Assistants, natural language and voice processing, classification, semantic search and information extraction, added to a product where they remove real manual work.
- LLM-backed features
- Semantic search
- Information extraction
- Recommendation systems
AI-powered applications & automation
Products where the model is the product. Cost, latency, model choice, reliability and data security are design inputs from the first week, not a later problem.
- Process automation
- Content generation
- Human review loops
Custom AI workflows
Model-backed pipelines built around an existing business process rather than beside it, with evaluation in place so quality is measured rather than described.
- Pipeline design
- Evaluation harnesses
- Cost & latency budgets
Data architecture & databases
A database is a foundation, not a storage location. Data structures are designed around how the product will actually be used, and around where it is going.
- Data modelling
- Indexing & caching
- Replication
- Scaling & optimisation
Advanced system integrations
Connecting products to the systems around them — payment, messaging, ERP, mapping, hardware — with the failure behaviour designed as carefully as the happy path.
- Third-party APIs
- Webhooks & queues
- Failure handling
Quality assurance & automated testing
Automated coverage where it pays for itself, plus structured sessions with the people who will actually use the software.
- Test automation
- Regression suites
- Release verification
AR/VR & emerging technologies
Real-time 3D, immersive experiences and experimental technology, used where it explains something the flat interface cannot.
- WebGL & 3D scenes
- Immersive experiences
- Static fallbacks
The same sevenStages.
The same sequence runs whether the engagement is four weeks or four quarters. Only the depth of each stage changes.
Discover
Business goals, users, workflows, constraints and the existing system. We write down what is true before proposing anything.
Strategize
Scope, sequence and the technical direction. Architecture and stack are decided here, after the problem — never before it.
Design
Flows and interfaces designed against real content and reviewed in the browser, with data model and interface moving together.
Build
Short cycles and working software each time. Frontend, backend, data and infrastructure are built as one system, not four.
Test
Automated coverage where it pays, security and performance checks, and structured sessions with the people who will use it.
Launch
Deployment, migration and the handover of a system your own team can operate, with monitoring in place before release.
Grow
Measurement, iteration, new capabilities and scaling. Most of a product’s real life happens here.
