AI Policy Automation

If your operations team is manually reviewing hundreds of transactions a day, cross-referencing contracts, SOPs, or compliance rules before anything can move. You are paying a significant and largely invisible tax on your own business. 

Order operations teams at manufacturers and distributors, claims handlers at insurers, compliance analysts in financial services, and procurement specialists in complex supply chains all face the same problem: the rules that govern their work live in documents, not systems. Thoughtworks eliminates that overhead with a production-proven agentic AI workflow built natively on Azure AI Foundry.

What changes when you deploy this

• Your team stops reading policy documents and starts approving AI recommendations: review time drops from approximately 60 seconds to 10 to 15 seconds per transaction
• The same rules apply consistently to every transaction, every time, not interpreted differently by whoever is on shift
• When contracts or SOPs change, the system updates without an IT release cycle
• Every recommendation shows the exact policy clause, current value, and proposed change. Full explainability at every step, no black box.
• Your team stays in control: the AI recommends, a human approves, and a complete audit trail is maintained for every decision

Results from a live enterprise deployment

This is not a proof of concept. Thoughtworks built and delivered this capability in production at a Fortune 500-serving global IT solutions provider on Azure AI Foundry. Within weeks of go-live:

• 88 to 90% AI recommendation accuracy in live operation, measured against human approvals
• 400+ person-hours saved within weeks of go-live across a 27-account enterprise customer base
• ~$2M per year of manual back-office effort now addressable through automation
• Adoption doubled in a single month as operator trust in the recommendations grew
• Microsoft co-funded approximately 60% of Phase 1 cost via ECIF, significantly reducing net client investment

How it works: four stages on Azure AI Foundry

• Interpret: your SOPs and contracts are converted into structured logic stored in Azure Cosmos DB. No manual rule coding. Policy updates are versioned without IT release cycles.
• Detect: transaction events captured via Azure Service Bus. Reliable, decoupled, horizontally scalable.
• Recommend: an Azure OpenAI GPT agent receives each transaction alongside its applicable policies and returns a validated, evidence-grounded recommendation.
• Approve: recommendations staged in Azure SQL, never auto-applied. Your team reviews and approves through your existing operational system.

What to expect: most clients are live within 12 weeks

• Weeks 1 to 3 Discover and Shape: Policy audit, Azure architecture design, and ECIF co-funding application submitted on your behalf.
• Weeks 4 to 14 Build and Prove: 3 to 5 policy touchpoints live in production, human reviewers approving AI recommendations from week 10, Power BI impact dashboard included.
• Ongoing Scale and Expand: Additional touchpoints, business units, or geographies on the same reusable platform.

Final pricing varies by number of policy touchpoints in scope, SOP complexity, number of upstream transaction systems, and Azure infrastructure requirements.

Built for regulated and high-stakes environments

Human-in-the-loop is a structural property of this architecture, not a configuration option. The AI cannot execute any transaction change autonomously. When confidence is insufficient due to ambiguous policy, missing data, or conflicting rules, no recommendation is generated and the transaction routes to standard manual handling.

Start with a no-obligation 5-day scoping assessment

We will identify your highest-value policy touchpoints, size the automation opportunity in hours and cost, and outline an ECIF co-funding path with Microsoft. Contact us today.