Modular & API-first
Each capability is an independent service with a clear interface — replaceable and extensible.
Architecture you can test, govern and change.
Technical teams should be able to see where data comes from, what a model can access, where an action stops and how quality is measured after release.
Architecture approach
Four decisions we make explicit at the start
Service boundaries, data ownership, model dependence and evaluation are settled before implementation.
Data & system connectivity
Secure connections to your existing software through APIs, databases or file flows.
Model independence
A separate model layer keeps dependence on any single provider to a minimum.
Knowledge & RAG
Source-grounded retrieval that tracks where every answer came from.
Agents & control
An agent does not enter operations without a defined boundary
Allowed tools, inputs and actions are explicit. Sensitive operations pause for the responsible person to approve them.
Data & security
Security is part of the first diagram
Access control, secrets, audit records and deployment location are designed early and documented for the project.
Role-based access control
Users only reach the data and actions their role allows.
Event logging
Important actions are logged for review.
Secrets management
Keys and sensitive values are kept out of code, with restricted access.
Backups
A backup plan matched to how critical the data is.
Deployment by requirement
Where it runs is decided by your confidentiality requirements.
Quality cycle
Quality changes in use, so evaluation continues
Fixed test sets, user feedback and production failures reveal drift, regressions and cost changes early.
- 01
Testing
Test scenarios and independent data before release.
- 02
Monitoring
Tracking performance, errors and cost in production.
- 03
Model evaluation
Answer quality, bias review and source tracing.
- 04
Continuous improvement
Refinement driven by data and user feedback.
Deployment scenarios
Data constraints decide where the system runs
Public cloud, private cloud or on-premise follows a review of data sensitivity, access, cost and your ability to operate it.
Cloud
The fastest way to start, for data with lighter confidentiality constraints.
- Faster setup
- Simple scaling
Private cloud
Dedicated infrastructure with tighter control over data and access.
- Isolated resources
- More control
On-premise
Deployed in your own infrastructure for strict requirements.
- Data stays in-house
- Hardware review required
Technical session
A simple systems diagram is enough to start
We can review data sources, existing APIs and security constraints, then make the trade-offs visible before proposing a build.
