AI automation services for businesses, built on secure foundations.
Most businesses don't need an AI strategy deck. They need Copilot switched on safely, a few well-built assistants that answer from their own data, and the repetitive processes that eat their team's week automated. We do all three, with the same security discipline we apply to the rest of your IT.
AI is only as safe as your permissions
AI assistants like Microsoft 365 Copilot can see everything the user can see. In most organisations that includes years of files shared with "everyone", forgotten SharePoint sites and mailboxes with loose permissions. Switch on AI without tidying that up and a casual question can surface salaries, HR cases or client contracts.
The second risk is shadow AI: staff pasting client data into free consumer chatbots because the business hasn't given them an approved alternative.
So every AI engagement starts with a readiness review: who can see what, where sensitive data lives, which tools people are already using, and what policy and controls are needed before anything is rolled out.
AI readiness review
- Oversharing audit across SharePoint, OneDrive and Teams.
- Sensitivity labels and DLP to keep confidential data out of AI answers.
- Shadow AI assessment: which tools staff are using today.
- AI acceptable use policy written for your business.
- Licensing advice: who needs what, and who doesn't.
- A prioritised list of use cases with realistic value and effort.
Copilot, rolled out so people actually use it
Microsoft 365 Copilot works inside the apps your team already uses: summarising Teams meetings, drafting in Word and Outlook, analysing Excel data and finding information across your tenant. It's powerful, it's a significant per-user cost, and it's only worth it if it's set up and adopted properly.
- Readiness: permissions, labels and data governance fixed first.
- Pilot group: licences for the roles that will benefit most, measured over a few weeks.
- Copilot Chat: getting value from the Copilot Chat included with Microsoft 365 before buying licences.
- Training: practical, role-specific prompting sessions for your team.
- Review: usage data to decide where to expand and where to cut back.
Copilot readiness
AssessmentOversharing audit, sensitivity labels, Purview and DLP configuration, and licensing plan.
Pilot & rollout
DeploymentLicences assigned, training delivered and adoption measured, with a clear go or no-go decision.
Copilot Studio agents
BuildCustom agents inside Teams and Copilot that answer from your SharePoint policies, procedures and knowledge base.
AI agents that do real work
An AI agent is an assistant that can do more than chat. It can look things up in your systems, follow a process and take actions, with a human approving the steps that matter. We build agents on the platform that fits the job: Copilot Studio inside Microsoft 365, or Claude, ChatGPT and Azure OpenAI where more flexibility or capability is needed.
Policy & knowledge assistant
Staff ask questions in Teams and get answers from your current handbook, procedures and product information, with sources linked.
Helpdesk triage
Common requests like password resets, access requests and "how do I…" questions answered or routed automatically.
Quotes & proposals
First drafts of quotes, proposals and tender responses assembled from your pricing and past work.
Inbox agents
Shared mailboxes read, classified and actioned: orders keyed, queries answered, exceptions escalated.
Candidate screening
CVs summarised and matched against the brief, with notes written back to your CRM.
Document extraction
Invoices, delivery notes and forms read and turned into structured data for your finance or ERP system.
Connect AI to your business systems with MCP
The Model Context Protocol (MCP) is an open standard for connecting AI assistants to tools and data. Instead of building a one-off integration for every AI product, a system is exposed once through an MCP server. Any compatible assistant can then use it, including Claude, ChatGPT and Microsoft Copilot Studio.
In practice, that means your team can ask an assistant to look up a customer in the CRM, check stock, raise a ticket or pull last month's figures, and it can do so from the live system rather than a stale export.
How we build MCP integrations
- Least privilege: read-only by default, with write actions added deliberately.
- Human approval for anything that changes data or sends something externally.
- Per-user identity, so the AI can only reach what that person is allowed to see.
- Logging of every request, so you can see exactly what the AI did and why.
- Vetted servers only: we review or build MCP servers rather than installing unknown ones from the internet.
Systems we can connect
- Microsoft 365: SharePoint, Outlook, Teams, OneDrive.
- CRM and ATS platforms with an API.
- Ticketing and helpdesk tools.
- Accounting and ERP systems.
- SQL databases and internal line-of-business apps.
- File stores and document libraries.
Automate the processes your team repeats every day
Not everything needs AI. Many of the biggest wins come from plain automation: moving data between systems, chasing approvals and generating documents. We choose the right tool for each job, then add AI only where it helps, such as reading unstructured emails or PDFs.
Power Automate & Power Platform
The natural choice inside Microsoft 365. Approvals in Teams, SharePoint workflows, Outlook and Forms automation, and Power Apps for simple internal tools, all within your existing tenant and security.
n8n, Make & Zapier
For workflows that cross many non-Microsoft apps. n8n can be self-hosted when data needs to stay under your control. Make and Zapier suit quick, lightweight integrations between SaaS tools.
AI inside the flow
Claude, ChatGPT or Azure OpenAI steps that classify emails, extract data from documents, summarise and draft, with a human review step where accuracy matters.
Processes we commonly automate
Joiners & leavers
Accounts, licences, groups, devices and equipment requests triggered from one HR form.
Invoice processing
Invoices read from the inbox, matched and posted to accounts for approval.
Lead handling
Website and email enquiries captured, enriched and routed to the right person in seconds.
Document generation
Contracts, reports and proposals produced from templates and system data.
Approvals
Purchase, holiday and expense approvals in Teams, with an audit trail.
Scheduled reporting
Weekly and monthly reports compiled and sent automatically.
Responsible by design
AI adoption goes wrong when it's rushed. Every solution we build includes:
- Clear data boundaries: which data an assistant can use, and where it's processed.
- Business-grade services whose terms exclude using your data to train public models.
- Human-in-the-loop for decisions and anything customer-facing.
- Audit trails for agent actions and automations.
- UK GDPR in mind from the start, alongside your own data protection responsibilities.
A workshop to map where time goes and which tasks are good candidates.
Permissions, data and policy put in order before anything is switched on.
One or two high-value use cases built and tested with real users.
Extend what works, train the team, measure the results and support it.
AI & automation questions
Is our data used to train AI models?
Microsoft states that Microsoft 365 Copilot doesn't use your organisation's data to train its foundation models, and business and API offerings from OpenAI and Anthropic don't train on your data by default. We use business-grade services and check the terms for each solution.
Does everyone need a Copilot licence?
No. We usually start with Copilot Chat, which is included with Microsoft 365, and a small pilot group on full licences. Usage data then shows where licences are worth paying for.
What is MCP?
The Model Context Protocol is an open standard that lets AI assistants connect to business systems and data through a consistent interface. It means one well-secured integration can work with several AI tools, including Claude, ChatGPT and Copilot Studio.
Should we use Power Automate or n8n?
If the process lives mostly in Microsoft 365, Power Automate is usually the right choice. For workflows across many third-party apps, or where self-hosting matters, n8n is often better. We recommend based on your systems, not a preference.
Are we too small for AI?
No. Smaller businesses often see the fastest returns, because a few hours saved each week is a large share of a small team's time. We start with one clear use case and prove the value before going further.
How long does a first project take?
A readiness review and a first pilot can typically be delivered in weeks rather than months, depending on the state of your data and permissions.
Which AI platforms do you work with?
Microsoft 365 Copilot and Copilot Studio, Power Automate and the Power Platform, Claude, ChatGPT and Azure OpenAI, and n8n, Make and Zapier for workflow automation.
Find your first AI win
Tell us which tasks eat your team's week. We'll show you what's realistic to automate, what it would take and what it's worth.