AI pilot & implementation
AI implementation services
We design, build, integrate and evaluate AI solutions that run inside your existing systems and workflows — with the testing, documentation and handover needed to keep them running after we leave.
Who this is for
- Organisations with an agreed AI opportunity that now needs building
- Teams whose prototype works in a demo but not in day-to-day operations
- Businesses with high-volume document, data or customer-contact workloads
- Organisations that need AI work to fit existing security, audit and access rules
The problem it solves
Building a prototype is only part of the challenge. Production introduces integration, security, governance, reliability and adoption requirements: real documents are messy, real users behave unpredictably, and real systems have access controls, audit requirements and downtime.
Without evaluation and monitoring, nobody can tell whether the system is still accurate six months later — so it quietly stops being trusted and stops being used.
What we do
- Design the solution around the workflow it has to fit, not the other way round
- Build a focused pilot and test it against agreed success measures
- Integrate with your systems and data, including on-premise where data cannot leave your infrastructure
- Put evaluation, logging and human review in place so results can be checked
- Support deployment and hand over documentation your team can maintain
What you receive
- Solution design
- Rapid pilot or prototype
- System and data integration
- Evaluation and testing
- Deployment support
- Documentation and handover
How the engagement works
- 01
Design
Agree the workflow, the success measures and the integration points.
- 02
Pilot
Build a focused version and test it on real work with real users.
- 03
Integrate
Connect to systems and data, with access control and audit logging.
- 04
Handover
Deploy, document, train the people who will run it and measure performance.
What a typical engagement looks like
Larger programmes are scoped individually, based on the systems involved, integration and data requirements, security and governance obligations, and how delivery needs to be run alongside your own teams.
Relevant delivery experience
Common questions
- Can the solution run inside our own infrastructure?
- Yes. The delivery experience behind Raga AI includes on-premise and in-tenant work where data cannot leave controlled infrastructure, as well as cloud platforms.
- How do you measure whether it works?
- We agree success measures before the build and evaluate against them, including accuracy, throughput and the time saved in the workflow.
- Who owns the solution?
- Ownership and licensing arrangements are agreed as part of each engagement. Where appropriate, this can include handover of project source code and documentation, subject to the agreed contract and any pre-existing or third-party intellectual property. Client-specific deliverables, our own pre-existing tools, open-source components, third-party services and AI model providers may each carry different licensing terms, and we set these out before work starts.
- Do you work alongside our in-house developers?
- Yes. We can lead delivery or work as part of your existing team.
Turn the strongest opportunity into something that works
Request a discovery conversation and we will talk through the workflow, the systems involved and what a first pilot could look like.
No generic pitch. No obligation to proceed.