Copilot Studio agents
Custom agents with topic design, conversational flow, escalation paths, and clear boundaries on what the agent will and will not attempt.
AI agents and copilots
Agents that act, not just answer.
We design AI agents that are grounded in your approved knowledge, connected to the systems where work actually happens, and governed so that security, oversight, and evaluation are part of the build rather than an afterthought.
The problem
What usually brings people here
If more than one of these is familiar, they are probably connected. We look for the underlying cause before proposing a build.
- Answers live in too many placesPeople search SharePoint, Teams, email, and line-of-business systems for information that should take seconds to find, and they still end up asking a colleague.
- Pilots that never reach productionA promising demo stalls because nobody agreed on data boundaries, review responsibility, environment strategy, or how the agent gets improved after launch.
- Assistants that cannot do anythingA chat experience that only summarises text creates little value. Business users need agents that submit requests, update records, and trigger approvals.
- Unclear oversight and risk postureSecurity, legal, and compliance teams block rollout when they cannot see what an agent can read, what it can do, and how its behaviour is monitored.
Capabilities
What we build
Knowledge grounding
Curated grounding on approved SharePoint, Dataverse, and enterprise sources with source citations and content freshness rules.
Business actions and orchestration
Power Automate and connector-based actions so an agent can create a request, update a record, or start an approval instead of describing how to do it.
Microsoft 365 Copilot extensibility
Declarative agents and connectors that extend Copilot into your own content and processes, plus practical readiness and adoption planning.
Azure AI integration
Azure AI services for document understanding, classification, and specialised reasoning where a low-code agent alone is not the right tool.
Evaluation and human oversight
Test sets, review workflows, feedback capture, and monitoring so quality is measured continuously rather than assumed at go-live.
Delivery approach
How the work runs
A repeatable path from an unclear problem to a system someone owns. The lifecycle decisions happen early, where they are cheap.
Discover
Identify the highest-value scenarios, the systems of record involved, the questions people actually ask, and the risk and governance constraints.
Design
Define agent scope, grounding sources, actions, escalation, identity and permission model, and the evaluation criteria for success.
Build
Implement in a governed environment with source control and managed deployment, then validate against the agreed test set with real users.
Evolve
Monitor usage, review unanswered and misrouted questions, expand actions, and improve grounding on a regular cadence.
Technology ecosystem
Product names are used descriptively. The right combination is decided during design, not assumed at the start.
- Copilot Studio
- Microsoft 365 Copilot
- Azure AI
- Power Automate
- Dataverse
- Microsoft 365
- Microsoft Entra ID
Outcomes
What changes afterwards
Faster access to trusted answers
People find approved information in one place instead of searching across disconnected systems.
Fewer manual handoffs
Routine requests are completed inside the conversation instead of becoming another ticket or email thread.
A defensible governance position
Security and compliance stakeholders can see grounding scope, permissions, action limits, and monitoring before rollout.
A repeatable path to the next agent
Environment strategy, patterns, and review processes carry forward, so the second agent is significantly cheaper than the first.
Related work
AI Agents • Microsoft Copilot
Enterprise Knowledge Agent
National research organisation
A governed Copilot Studio experience that answers policy and procedure questions from approved sources, cites where each answer came from, and hands routine requests straight into the systems that process them.
View case study
Automation • Azure • AI Agents
Document Automation Service
Regulated services provider
An Azure service that classifies and extracts data from inbound documents, routes low-confidence cases to a human, and writes verified results into the business system.
View case study
Related insights
AI Agents
Governing enterprise AI agents
A practical approach to grounding, permissions, evaluation, and human oversight — the four decisions that separate an agent pilot from an agent in production.
Ahmed Salih5 min read
Questions
Frequently asked
Three controls do most of the work. First, grounding is limited to approved sources with an owner and a review cadence, so the agent cannot cite stale or unvetted content. Second, the agent inherits the user's existing permissions rather than a broad service account, so it cannot surface content the person could not already open. Third, we build an evaluation set of real questions before launch and re-run it after every meaningful change, which turns quality into something you measure rather than something you hope for.
They solve different problems and often run together. Microsoft 365 Copilot helps with broad productivity work across mail, documents, meetings, and chat. A custom Copilot Studio agent is the better choice when you need a specific process, a controlled knowledge boundary, or the ability to take actions in a line-of-business system. We usually recommend confirming the business scenario first, then choosing the tool it points to.
A short discovery to select and scope one scenario, followed by a working agent in a governed environment that a real user group can test. The goal is a production path rather than a demo, so the first build includes the environment strategy, permission model, action design, and evaluation approach that later agents will reuse.
We recommend naming three roles before go-live: a business owner for scope and content, a technical owner for the environment and integrations, and a reviewer who looks at unanswered or misrouted questions on a set cadence. Agents drift when content changes and nobody notices, so a light ongoing review is more valuable than a heavy one-time launch process.
Let's talk
Let's talk about AI Agents & Copilots.
Bring the problem rather than a specification. A short conversation is usually enough for us to tell you what we would do first — and whether we are the right people to do it.
Prefer email? info@aqlyst.ai