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AdySphere Co.

AI Enablement

AI that works for you. Not more workload, not more overheads.

Most AI arrives as another tool to check. We enable AI inside the systems your teams already run, so it reads live data, acts within your security, and closes the gaps where data and money leak.

Two ways in. One standard.

Built into Microsoft Dynamics 365

Already on a Microsoft Dynamics 365 tenant.

  • Built on Dataverse, Copilot Studio and Power Automate, with Claude for deeper reasoning
  • Works across Microsoft Dynamics 365 apps, Teams, Outlook and Power BI, where people already work
  • Uses the security roles and approvals you already run
  • The shortest path to production, because the data and processes are already there

Custom, built on Claude

For businesses on any other stack.

  • Custom AI architecture built on Claude, designed around the demands of your industry
  • Connects to SAP, Oracle, Zoho, other ERPs and in-house systems through APIs
  • Same governance: your cloud, your access rules, a full audit trail
  • No ERP replacement required to start

AI enablement is not AI usage.

Using AI means more tools, more prompts and more output to check. Enabling AI means the work itself gets shorter.

Typical AI usage

AI Enablement

  • A chatbot for every task

    One shared layer across every department

  • Data copied out to an AI tool

    Works on live data, inside your tenant

  • Answers someone has to check and re-key

    Drafts the next action in the system, ready to approve

  • Reports that look backwards

    Flags what needs a decision before it is late

  • Spend measured in prompts and seats

    Value measured against a baseline set in the Blueprint

One layer. Every department sees across the business.

A finance question often needs project data. A service answer often needs the contract. Because every department plugs into the same layer, the answer comes from the whole business, not one silo.

Shared AI layerin your tenant

Finance

“Which projects will go over budget this month?”

Flags projects heading over budget before month-end, with the entries driving the overrun, so finance acts before the close instead of explaining it after.

Every department plugs into the same layer, so each one sees across the business. A person approves the actions that matter.

Your data stays in your tenant.

  • Inside your tenant

    It runs in your Microsoft environment. Your data does not move to a separate AI tool.

  • Your security roles

    It sees only what the person asking is allowed to see, using the access you already manage.

  • People approve

    Actions that matter wait for a person. You decide where approval is needed.

  • Full audit trail

    Every answer cites its sources, and every action is logged. Its memory is a record you can see and edit.

Start small. Prove value. Scale.

  1. AI Enablement Blueprint

    Map your systems, data and key decisions. Pick the first department where AI pays back most, and set the baseline.

  2. Deploy

    Put the shared AI layer and the first department live, inside your tenant, connected to your systems.

  3. Extend

    Add departments one by one. Each one plugs into the same layer, so each makes the others more useful.

  4. Run

    We monitor, tune and grow it as your business changes, and report on the value it delivers.

Start with an AI Enablement Blueprint.

A clear map of where AI pays back first in your business, and what it takes to get there.

Plan a Blueprint