AI agents on Dynamics 365
Voice. Triage. Back-office. Grounded in your data.
Microsoft 365 Copilot is the starting line. We build custom agents — voice intake on Azure Communication Services, triage copilots inside Customer Service, and document-processing flows on Azure OpenAI — that actually move case-handle time, lead conversion, and back-office throughput.
What “done” looks like
A working agent deployed in your tenant
Grounded against your Dataverse + SharePoint
Telemetry + cost dashboard in App Insights
Eval harness for accuracy & drift, in your repo
Documented runbook for the team that runs it
Agent patterns we build
A handful of patterns we’ve shipped before, ready to adapt.
Voice intake
A real-time voice agent that opens, classifies, and routes a case while the caller is still on the line. ACS + Azure AI Speech + your Customer Service queues.
Triage copilot
Inside Customer Service. Summarizes the inbox, scores by impact, and proposes the next action — with a one-click commit back to the case.
Lead enrichment
Web research + your CRM history merged into the new-lead record before sales sees it. Reduces SDR ramp and dedup busywork.
Document extraction
Invoices, packing slips, vendor docs. Extract → match → route to the right approver. Reconciles to PO inside Business Central.
Self-serve portal copilot
Power Pages portal-side agent answering customer questions, opening tickets, and reading their own order/case history from Dataverse.
Back-office workflow agents
Power Automate + Azure Functions + LLM checks. Exception-handling for AP, AR, and inventory adjustments — with an audit trail a controller can sign off.
How we build
Engineered, evaluated, and run on your tenant.
Inside your boundary
Azure OpenAI in your subscription. Your prompts, your data, your retention policy. No third-party data exhaust.
Evaluated before deployment
Every agent ships with an offline eval set: accuracy, refusal-rate, hallucination on edge cases, latency. We don’t guess — we measure.
Auditable in production
Structured prompt + response logs to App Insights, with sensitive fields redacted at the boundary. Token cost and call-rate dashboards out of the box.
What we won’t build
Some honesty about where AI doesn’t belong yet.
We’ll tell you no when it makes sense. A few examples of things we’ll politely decline and recommend a non-AI path instead:
- Closed-book financial advice or anything that should ladder back to a regulated process.
- Open-ended autonomous agents that take irreversible actions without human review.
- Anything where the cost of a wrong answer is greater than the cost of just doing it manually for now.
Intent acc.
96.4%
Slot-fill
92.1%
Refusal
99.8%
240 prompts across 12 case types. Drift threshold < 1.5% week-over-week before alert. Eval set versioned in your Azure DevOps repo.
Scope a 4–8 week AI pilot
One case type, one queue, one fixed fee. We’ll come back with a baseline, a target accuracy, and a pilot plan you can underwrite.