Anyone can demo an agent. Fewer can make one trustworthy.
The first Copilot Studio agent takes an afternoon. Making it answer correctly on the hundredth question, refuse gracefully on the ones it should not touch, and still be maintainable a year later is the actual work. LogiSam builds agents grounded in your own content — with evaluation, guardrails and measurement from the start.
Where AI projects usually come unstuck
Almost none of these are model problems. They are content, scope and governance problems wearing an AI costume.
Book an AI use-case workshop- The demo was brilliant. The pilot answered three questions wrong and lost the room.
- The agent quotes a policy that was replaced eighteen months ago.
- Someone built a bot on a personal account and it is now in front of customers.
- You bought Copilot licences and cannot tell who is actually using them.
- Legal will not sign off because nobody can say what data the agent can reach.
- Every department wants an agent and there is no way to decide which one is worth building.
What separates a pilot from production
The technology is the commodity. Grounding, evaluation, guardrails and measurement are what make an agent something you can put in front of staff or customers.
Grounding beats prompting
An agent is only as good as the documents behind it. We curate the knowledge sources, fix the duplicates and retire the superseded content before writing a single instruction.
Evaluated, not just tested
A test set of real questions with expected answers, scored before and after every change — so you know whether the last tweak helped or quietly broke something.
Guardrails that hold
Scoped knowledge, explicit refusals, DLP, environment policy and an approval path — so the agent stays inside the boundary when someone asks it something creative.
Measured from day one
Usage, containment, deflection and licence utilisation instrumented at launch, because the renewal conversation is twelve months away and arrives fast.
What we build
From a single departmental agent to a governed Copilot programme across the tenant.
AI use-case discovery
Score candidate use cases on value, data readiness and risk, then pick the one that will survive contact with real users. Deliverable: a ranked AI roadmap, not a wish list.
Copilot Studio agents
Agents grounded in SharePoint, Dataverse, Graph or an API, with topics, actions, authentication and Teams distribution. Deliverable: a published agent with an owner.
Microsoft 365 Copilot roll-out
Readiness, licence targeting, persona use cases, pilot cohort and phased enablement. Deliverable: Copilot in the hands of the people who will use it.
Custom AI on Azure
Azure AI Foundry, Azure OpenAI, AI Search and custom RAG when Copilot Studio is the wrong shape. Deliverable: a solution that fits the problem rather than the tool.
Evaluation & red-teaming
Question sets, scoring, hallucination and refusal testing, and adversarial prompts before your users find them. Deliverable: evidence for the sign-off meeting.
Agent governance & lifecycle
Ownership, approval, review and retirement for every agent, plus tenant-wide inventory. Deliverable: no shadow agents.
Know what your AI is doing — and what it costs
Once agents and Copilot licences start multiplying, the questions get uncomfortable: how many agents are there, who owns them, what data do they touch, and are the licences we bought actually being used? Copilot Insights answers all four from a read-only scan that reads activity metadata only — never prompt content — so security sign-off takes a day rather than a quarter.
- Automatic inventory of every Copilot Studio and custom agent in the tenant
- Owners, channels and knowledge sources for each one — no more shadow agents
- Unused, orphaned and sensitive-data agents flagged for review
- Purchased versus assigned versus actively-used licences, with reclaimable spend
- Adoption over time, per surface and per department
- Board-ready ROI exports for IT, security and finance
Read-only · activity metadata only · never prompt content
How an agent gets built
- 1
Choose
One use case with a clear owner, real questions and content that already exists.
- 2
Prepare
Curate and clean the knowledge. This is where most of the quality comes from.
- 3
Build
Instructions, topics, actions and authentication in Copilot Studio or Azure.
- 4
Evaluate
Score it against the question set. Iterate until it is right, and prove refusals work.
- 5
Launch & watch
Publish to Teams, instrument usage, review the transcripts, improve on evidence.
What you walk away with
Every engagement ends with something you can use — not a slide deck.
- A published agent with a named owner and a documented knowledge scope
- An evaluation set you can re-run after every change
- Guardrails, refusal behaviour and DLP tested before launch
- A tenant-wide inventory of every agent already running
- Usage and containment reporting from launch day
- A ranked roadmap of the next use cases worth building
Ways to start
AI use-case workshop
Half a dayBring the ideas. We score them on value, data readiness and risk, and tell you which one to build first.
- Ranked use-case list
- Data readiness view
- Realistic effort per option
First agent
2–4 weeksOne grounded, evaluated agent published to Teams, with the guardrails and measurement in place.
- Curated knowledge sources
- Evaluation set and scores
- Owner, guardrails and telemetry
Copilot programme
OngoingTenant-wide Copilot roll-out, an agent factory and the governance to keep both under control.
- Phased licence roll-out
- Agent approval and lifecycle
- Adoption and ROI reporting
Built on
Trusted by teams at
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Copilot, AI & chatbots: your questions answered
What is the difference between Microsoft 365 Copilot and Copilot Studio?
Microsoft 365 Copilot is the licensed assistant inside Word, Outlook, Teams and the rest — it reasons over your tenant content and you configure rather than build it. Copilot Studio is where you build your own agents: your knowledge sources, your instructions, your actions into other systems, published to Teams, a website or a phone line. Most organisations need both, for different jobs.
Will an agent make things up?
It will if you let it. Grounding the agent in specific, curated knowledge sources, constraining it to answer only from them, and evaluating it against a test set of real questions is what separates a usable agent from a demo. We build the evaluation set before we build the agent.
How do you stop a chatbot leaking data it should not see?
Two layers. The agent inherits the permissions of the person asking, so your SharePoint permissions have to be right first — which is why we usually start with a SafeScan. Then the agent itself is scoped to named knowledge sources rather than the whole tenant, with DLP and environment policy around it.
How long does it take to build an agent?
A first useful agent over a defined set of documents takes two to four weeks including evaluation. Agents that take actions in other systems — raise the ticket, book the leave, update the record — take longer, because the integration and the failure handling are the real work.
Should we use Copilot Studio or Azure OpenAI?
Copilot Studio when the agent lives in Microsoft 365, needs Teams distribution and should be maintainable by someone who is not a developer. Azure AI Foundry and Azure OpenAI when you need custom orchestration, your own vector store, unusual models or an experience outside Microsoft 365. We will recommend the boring option whenever it fits.
How do we prove Copilot is worth the licence spend?
Measure it. Copilot Insights shows active usage per surface and per user, dormant licences and reclaimable spend, with an executive summary for finance. Without measurement, Copilot renewal becomes an argument about anecdotes.
Do you help with the roll-out and training too?
Yes — see user training and adoption, delivered with our partners Sahaba Club and ImpactEra. Prompt craft is a learned skill, and the gap between a trained and untrained user is larger than the gap between two AI models.
Start with the use case, not the technology
Bring us three ideas. We will tell you which one has the content behind it to work, which one is a governance problem first, and which one you should not build at all.
UK & UAE · Microsoft Solutions Partner · Copilot Studio, Azure AI and Microsoft 365 Copilot