AI services
Practical AI for your teams and operations
We help mid-market and regulated organizations adopt AI the same way we deliver managed IT: with a clear scope, secure design, and measurable outcomes. No science projects — production use cases that fit your infrastructure and compliance needs.
AI that fits your IT — not the other way around
Most businesses do not need another experimental chatbot. They need Microsoft 365 Copilot rolled out safely, internal knowledge made searchable without leaking data, and routine work automated with clear human oversight. Outsource Information Systems designs, deploys, and supports these capabilities alongside your existing cloud, security, and managed services stack.
- AI readiness and use-case assessment
- Microsoft 365 Copilot and Azure OpenAI deployment
- Secure internal assistants grounded on your documents (RAG)
- Private or hybrid AI options for sensitive workloads
- Workflow automation with human approval steps
- Policies, access control, and audit logging for AI use
- Team training and change support
- Ongoing monitoring as part of managed services
What we deliver
Engagements are scoped like any other IT consulting project: discovery, design, pilot, production, and support.
AI strategy and readiness
Map where AI can reduce cost or risk in your processes, assess data readiness, and define a realistic roadmap with priorities and budget.
Microsoft Copilot adoption
License planning, security baselines, pilot groups, and adoption support for Microsoft 365 Copilot and related Microsoft AI tools.
Internal AI assistants
Assistants connected to approved knowledge bases so staff can find policies, procedures, and project information faster — with citations and access controls.
Private and hybrid AI
For regulated or confidential data, we design private cloud or on-premises options, including controlled model hosting and network isolation.
Process automation
Automate ticket triage, document drafting, reporting, and repetitive back-office tasks with clear escalation paths to your teams.
Governance & security
Acceptable-use policies, DLP alignment, logging, vendor review, and staff guidelines so AI use stays compliant and reviewable.
What sets us apart: we understand the environment AI runs on, from identity, cloud and Microsoft 365 to infrastructure, security, APIs, data and software development. AI services are delivered by the engineers who already run your infrastructure. Start with the AI workshop below.
AI workshop: identify your use cases
A practical workshop to identify 2 to 3 AI or automation opportunities in your company, and what needs to be in place to deploy them safely.
- Identify repetitive, time-consuming workflows
- Assess data and security readiness
- Shortlist 2 to 3 priority use cases (AI or automation)
- Estimate the return on investment of each
- Receive an implementation proposal
After the workshop, you receive a written summary of your use cases and an implementation proposal.
Where AI helps businesses today
The most useful AI projects in mid-sized organisations are rarely spectacular. They save time on writing, searching and summarising: drafting emails and reports, finding the right procedure in a shared drive, summarising meetings, or triaging support requests.
Tools such as Microsoft 365 Copilot can deliver that value quickly, provided your data is organised and your permissions are right. Otherwise, an assistant can surface documents to people who should never see them. That is why we treat AI as an IT and security project, not only a software purchase.
Keeping AI secure and compliant
Before rollout, we review who can access what in Microsoft 365, SharePoint and your file servers, and correct oversharing. We then define which AI tools are approved, what data they may use and how their use is logged.
For sensitive or regulated data, we design private or hybrid options where models run in a controlled environment and data does not leave your chosen boundary.
How an AI project runs
AI projects follow the same disciplined stages as any IT project:
Discovery
Workshops to identify tasks where AI saves time or reduces risk, and a review of your data and licences.
Readiness
Permissions clean-up, data classification and security baselines so AI tools only see what users are allowed to see.
Pilot
A limited group tests the chosen tools on real work, with success criteria agreed in advance.
Rollout
Wider deployment with training, usage guidelines and support.
Governance
Ongoing monitoring, policy updates and reporting on adoption and value.
Frequently asked questions
Is our data used to train public AI models?
With business offerings such as Microsoft 365 Copilot and Azure OpenAI, your prompts and data are not used to train the underlying public models. We check the terms of every tool before recommending it.
What do we need before deploying Microsoft 365 Copilot?
Suitable Microsoft 365 licences, well-organised data and correct permissions. Our readiness phase covers all three.
Can AI run on our own infrastructure?
Yes. For confidential workloads, we can host models in a private cloud or on-premises, with network isolation and access controls.
How do we measure the value of AI?
We define measurable goals during the pilot, such as time saved per task or requests handled, and report against them before a wider rollout.
Will AI replace our staff?
Our projects focus on removing repetitive work and helping staff find information faster. Important decisions stay with people, with approval steps built into automated workflows.
Start with the AI workshop
In 60 to 90 minutes, we identify 2 to 3 processes to automate with you, check that your data and security are ready, and estimate the return on investment.