AI Intelligent Apps
Microsoft AI Builder, Power Platform, Azure OpenAI and Copilot Studio applied to document processing, prediction and language work, embedded where people already work and governed so security and audit have answers.
If automation without AI would solve the problem more cheaply, we will say so before building a model.
Sound familiar?
Most organisations already have the licences. What is missing is a process chosen deliberately, tested on real data, and owned after go-live.
The document arrives as a PDF and somebody retypes it into the system every day.
The process is defined, but it moves at the speed of whoever is checking email.
A promising demo exists, and nothing in the business runs differently because of it.
Which means company information is leaving without anyone deciding that it should.
When an extracted value or a prediction is wrong, it is unclear who checks and who corrects it.
What we actually build
Low-code where low-code is enough, Azure OpenAI and Copilot Studio where language work genuinely needs it, governance throughout.
AI Builder models read invoices, forms, purchase orders and identity documents, extracting the fields your process needs and passing them into Dynamics 365 or the Power Platform.
What this gives you
Swipe, drag or use the arrow keys to move between decisions.
The underlying apps and flows are covered under Power Platform, and forecasting on operational data under predictive intelligence.
Microsoft Copilot
Copilot is an AI layer over the Microsoft 365 apps your people already open, grounded in the content they are already allowed to see, and governed by the controls you already run.
Copilot works across Word, Excel, PowerPoint, Outlook and Teams, drafting, summarising, analysing and catching people up on what they missed.
A chat surface on web, desktop and mobile for questions, drafting and research, available to eligible Microsoft 365 users without an added per seat cost.
Responses are grounded in Microsoft Graph, so Copilot reasons over the mail, files, meetings and chats the signed in person is already permitted to see.
Answers can draw on tenant content, on the open web, or on both, so the same assistant covers internal policy and external research.
Data access is always scoped to the signed in user's permissions and stays inside the Microsoft 365 service boundary. Your content is not used to train the foundation models.
Sensitivity labels, encryption, audit and Microsoft Purview controls apply to Copilot activity, and data residency commitments follow your tenant.
Copilot connectors bring line of business content into the index, and agents add specialist skills for a particular team or process.
A per seat Microsoft 365 Copilot licence, or usage based billing in Copilot Credits for Copilot Chat, SharePoint agents and Copilot Studio consumption.
Capability and licensing detail summarised from Microsoft Learn documentation for Microsoft 365 Copilot, Copilot Chat and Copilot Studio.
Custom agents
Copilot answers questions. An agent takes the routine work off the desk entirely: triggered by an event or a schedule, grounded in your own sources, acting through connectors and flows, and escalating to a person when it should.
Microsoft documents declarative agents and custom engine agents, and the choice sets how much control you take on.
We pick the most fitting option that does the job, because it is the cheapest one to own afterwards.
In detail
Microsoft documents declarative agents and custom engine agents, and the choice sets how much control you take on.
We pick the most fitting option that does the job, because it is the cheapest one to own afterwards.
Where this usually starts
We scope each agent against a real task and a real measure, so you can tell whether it earned its keep before you build the next one.
How we deliver it
Choosing the candidate, testing accuracy on real data and designing the human step matter more than the model itself.
The first candidate decides whether the programme continues, so it is chosen on volume, clarity and measurability.
If a Power Automate flow with no AI in it would solve the problem, we will say so.
In detail
The first candidate decides whether the programme continues, so it is chosen on volume, clarity and measurability.
If a Power Automate flow with no AI in it would solve the problem, we will say so.
Why InteliSense
The same team runs your Dynamics 365 and Power Platform, so the AI lands where the work already happens.
We start from the work being done today, because AI applied to a broken process makes it faster and no better.
Accuracy is demonstrated on your documents and history before anyone commits to a rollout.
AI Builder, Power Platform, Dynamics 365 and Azure OpenAI in your tenant, delivered by one accountable team.
Low confidence output goes to a person by design, so nobody has to trust a model unconditionally.
AI Builder credits and Azure consumption are modelled before the build, not discovered afterwards.
Models are monitored, retrained and retired with named ownership rather than left to drift.
Before you call
A conversation, not a demo
Tell us which task still involves retyping, chasing or manual checking. We will tell you whether AI is the right answer, what accuracy would need to be, and who would own it afterwards.
