Adverse-event root-cause analysis across 45 hospitals.
8 hrs / case<1 min / case
Eval design
Clinician-graded RCA rubric on historical cases; case-pack completeness; governance review.
+30% data captured · cycle time weeks → days
Microsoft Delta is a team of engineers, designers, and product managers embedded directly with customers that turns ambiguous business problems into production-grade agentic systems with measurable impact. If this sounds interesting, we’d like to learn more about you.
Apply nowOur impact
We don’t ship agents we can’t measure. Every engagement starts with an evaluation harness — graded by domain experts, replayed against historical decisions, and re-run on every release. Here’s what that looks like in production.
Specialty-drug denial appeal letters.
2–3 hrs / letter30 min / letter (4× throughput)
Eval design
3-axis rubric — factual (QAFactEval) · clinical (MedHELM) · payer-acceptance — graded weekly with humans.
+30% factual accuracy · scalable reimbursement workflow
Power-of-Attorney abuse investigations.
96% accuracy (human)96% accuracy (agent)
Eval design
Labelled past investigations; agent vs. human on the same cases; replay vs. historical outcomes.
65% manual effort eliminated · 2,500-case backlog cleared
Trade-claim validation.
~40% reviewed100% reviewed
Eval design
Replay vs. historical analyst override decisions; $-weighted scoring; audit-grade explainability.
$300M leakage recovered
Alt-fund historical onboarding to custody schema.
6 months2 weeks (target)
Eval design
Schema-mapping accuracy on labelled fund samples; HITL on ambiguous mappings.
$20–30M incremental revenue
Inbound chat lead routing & qualification.
F1 0.38F1 0.81
Eval design
~1k chat golden dataset; 3× class F1 + accuracy; re-run every release.
$20–40M unlocked pipeline
Returns-inspection agent — vendor chargebacks (60% of returns).
3% error<2% error (target)
Eval design
Per-measurement abs deviation vs. ground truth on labelled returns; tolerance-aware pass/fail (e.g. 2" waistband, 1.5"); vendor-chargeback acceptance rate.
Defensible chargebacks · multi-$M margin recovery
How we work
We embed directly with the customer, turning ambiguous problems into production agents end-to-end. We work alongside the customer through discovery and prototyping, then deploy directly into their tenant.
01
Discovery
Immerse in the customer's workflow, map the problem space, and identify where AI agents create measurable impact.
02
Prototype
Build a working prototype on real data to demonstrate speed, quality, and ROI potential.
03
Solution
Deploy a production-grade AI agent in the customer's tenant. Design custom evals and hill climb against real workflows to deliver measurable ROI.
We’re looking for engineers, designers, and product managers who want to build evaluable AI agents alongside Microsoft’s most strategic customers.
Apply now