Solution patterns
Problems We Solve, and How
Six patterns we build with Microsoft technology — the problem each one addresses, the approach we take, and the outcome it is designed to deliver.
Manufacturing
A Copilot Studio agent that answers the service desk's repeat questions
Designed to target
- of tier-1 tickets deflected
- 50–70%
- to a first response
- Seconds
- cover without added headcount
- 24/7
The scenario. Most IT tickets are password resets, software requests and 'how do I' questions. They consume the desk's capacity, first response stretches into hours, and evening cover is hard to staff.
The approach. A Copilot Studio agent grounded in the existing SharePoint knowledge base, with Power Automate actions for password reset and licence assignment, escalating to a human ticket whenever confidence is low.
Insurance
Azure AI Foundry reading document packs that are otherwise keyed by hand
Designed to target
- of fields extracted without review
- 85–95%
- to a structured record
- Seconds
- throughput per handler
- 2–4×
The scenario. Claims arrive as mixed packs of PDFs, photographs and scanned forms. Handlers spend the first several minutes of every claim transcribing fields before any assessment begins.
The approach. An Azure AI Foundry pipeline extracting structured fields, with a human-review queue for anything below the confidence threshold, writing straight into Dataverse for the existing handler app.
Utilities
A paper form pack replaced by one Power Platform field app
Designed to target
- replacing the paper pack
- One app
- job data reaching scheduling
- Live
- faster job completion
- 20–30%
The scenario. Field crews carry duplicate paper forms, and job data reaches the back office days late, so scheduling runs on stale information.
The approach. A single offline-capable Power Apps canvas app over Dataverse, with Power Automate posting completions to the scheduling system and Power BI reporting on first-time fix.
Professional services
A knowledge agent that finds the right past work in seconds
Designed to target
- of queries resolved without a human
- 70–80%
- faster proposal turnaround
- 15–25%
- sensitivity-label breaches by design
- Zero
The scenario. Consultants rebuild proposals from scratch because nobody can find comparable past work across years of accumulated SharePoint sites.
The approach. A Copilot Studio agent over curated SharePoint knowledge sources with sensitivity-label trimming, so it only ever surfaces material the person asking is cleared to see.
Financial services
Bringing unmanaged agents under Agent 365 governance
Designed to target
- of agents with a named owner
- 100%
- as the single source of truth
- One register
- controls on every agent
- Audit-ready
The scenario. Business teams build agents independently for months. Nobody holds a list, some builders have left, and none of it would survive an audit.
The approach. A full inventory through Agent 365, an accountable owner assigned to every agent, orphans retired, and a standard control set applied covering data access, logging and review cadence.
Logistics
Invoice handling reduced to exception handling
Designed to target
- straight-through processing
- 95–99%
- the only invoices a person sees
- Exceptions
- redeployed to higher-value work
- 2–4 FTE
The scenario. A shared service centre keys thousands of supplier invoices a month, and month-end close slips whenever someone is on leave.
The approach. Power Automate with AI Builder extraction, matching against purchase orders and posting straight through, routing only genuine mismatches to a person.
Have a Microsoft challenge worth solving?
Let's talk about how Ayka can help you build, automate, agentify, modernize and support your Microsoft environment.