Automating Order Intake in D365 with a Fractional Azure OpenAI Automation Expert

A leading North American food manufacturer relied on a shared “Orders” inbox where customers submitted purchase requests as free-form emails. Manually turning those emails into D365 sales orders consumed multiple team members and slowed the business down. The leadership team wanted to use AI automation—specifically Azure OpenAI—to streamline order intake in D365 without sacrificing accuracy, control, or security.

Rather than simply “filling a role,” our team sat down with the client’s IT leader to deeply understand the problem they were trying to solve. Together, we clarified where their current order intake process was breaking down, what AI-powered order processing in D365 would need to look like in practice, and then used that insight to identify the right fractional AI talent solution to drive a proof of concept.

The Ask

The client wanted a focused AI automation proof of concept that would:

Use Azure OpenAI (o3‑mini) and Power Automate to interpret unstructured order emails

Extract key order details (customer, product, quantity, ship-to, dates, etc.) and apply existing business rules and contract logic

Create draft sales orders in D365 with a human-in-the-loop review step

Deliver measurable accuracy and meaningful time savings for the operations team through AI-powered order intake automation.

How We Worked

Once the IT leader and our team aligned on the real problem and outcomes, we helped define the profile for a fractional Senior AI Automation Engineer and the specific objectives for their first 30 days. We weren’t just asked for “an OpenAI person”; together we shaped a clear mandate and success criteria so the engagement was grounded in business value and a practical Azure OpenAI automation strategy, not just technology.

We then placed a senior Azure OpenAI consultant who integrated directly with the client’s team. Working side by side with stakeholders across IT and operations, the consultant:

Co-designed prompts, logic, and workflows that reflected how the business actually thinks about customers, contracts, and orders

Extended the existing Azure OpenAI agent to parse incoming order emails and output structured, traceable order data for D365

Connected that data into D365 so draft sales orders were created automatically, with a streamlined review workflow instead of manual data entry

Tested and iterated with end users, refining the AI-driven order intake automation based on real-world edge cases and feedback from the people closest to the work.

All of this ran in the client’s secure Azure environment, honoring their data governance and “no public ChatGPT” requirements.

The Impact

The AI automation proof of concept was completed under budget and ahead of schedule, and it met the jointly defined accuracy and workflow goals. One reviewer can now manage the order volume that previously required a larger team, freeing skilled employees from repetitive keying and allowing them to focus on higher-value, business-driving work.

Off the back of this success, we’re partnering with the client to shape a longer-term AI automation roadmap for D365 order processing and the right mix of fractional and full-time AI talent to support it.