Beyond the model.Into the business.
Agents, knowledge systems and automation connected to your information and applications. The work is in the permissions, integration, evaluation and operation.
Explore the technologyBeyond the chat window.
Eight ways to put models to work. Connect the capability, define its authority and test what happens.
Computer-use automation
Controlled browser and desktop workflows for software without a suitable API.
Voice & visual assistants
Real-time conversation, visual context and tools connected to a useful workflow.
Multimodal knowledge
Search documents, diagrams, images and recordings with references to the source.
Connected agents
Specialist agents working across platforms, with defined handovers and results.
Agent identity & security
Defined ownership, scoped permissions and controls around execution.
State, memory & recovery
Long-running work with checkpoints, controlled memory and recovery.
Private & hybrid AI
Local, hosted and hybrid models with explicit data and network boundaries.
AI-assisted modernisation
Investigate code, build tests and prepare changes with engineers in control.
Model choice, controls and delivery are scoped around your systems.
Explore the foundationsA governed agent, layer by layer.
How we structure an AI agent that works inside the business. Every layer has a job, an owner and a limit.
People and requests
Every request carries the identity of the person who made it.
- Teams
- Web
- Voice
Agent runtime
Planning, memory and model routing, with one identity per agent.
- Orchestration
- Memory
- Model routing
Guardrails
Policy is enforced outside the model. Consequential actions wait for a person.
- Policy checks
- Approvals
- Evaluation
Tools
Each tool gets the narrowest credential that works.
- MCP servers
- APIs
- Computer use
Enterprise systems
Existing permissions are respected, never widened.
- Microsoft 365
- Line of business apps
- Databases
Evidence
Every step leaves a record you can inspect.
- Audit trail
- Traces
- Cost and quality metrics
Keep the foundations in view.
New capabilities still need well-designed data, interfaces, testing and operational ownership.
AI agents & automation
Tools, state, approval and recovery around a clearly defined task.
Enterprise knowledge & RAG
Access-aware retrieval, document processing and source-grounded answers.
AI integration & MCP
APIs, MCP tools and operational systems connected with explicit permissions.
Model orchestration
Model choice, context, routing and controlled fallback.
AI evaluation & governance
Representative tests, risk controls and measurable operational behaviour.
AI operations
Monitoring, recovery, cost control and ongoing engineering.
Prototype to production
Keep what works. Strengthen what production needs.