New playbook: when your own AI model pays. Read
DoorDash (delivery marketplace, ~20,000+ employees) reported this on 30 Jun 2026 in company self-report (source). It belongs to the agents, traceability and evals layer.
An evaluation harness for the multi-agent Ask DoorDash ordering assistant: rubrics per agent, a transcript builder, a conversation simulator and auto-grading of live sessions, used as the launch bar.
Quality signal grew from ~1 employee feedback report to 2,000 auto-graded sessions a day; agent quality score up 8 points and error rate nearly halved before nationwide launch; a manual regression test that took more than six hours now runs in ~20 minutes.
The number covers ask DoorDash agent, pre-launch and production evaluation.
“…we drove an 8-point improvement in agent quality scores ahead of nationwide launch,” DoorDash said.
Separate evals for routing, guardrails (trust and integrity) and per-agent capability; offline replay before any change; the harness validated a base-model swap that cut latency 35% without quality loss.
Each agent has one narrow task, a named owner and an action log.
Read the guide to agents, traceability and evals.
12,500
banker hours saved in the first month of operation, July 2026
Five specialist agents on Amazon Bedrock AgentCore that classify and read payslips and bank statements, run serviceability calculations and verify them against lending policy, then hand the banker a result to review for mortgage and credit-card applications (source).
$10M
EBITDA uplift from two agent systems, Partners Group says
Two agentic systems built on a cleaned proprietary policy-level dataset: one runs new-client policy processing, the other automates human-intensive policy checking; delivered by a seven-person team with Version 1 (source).
2–3 minutes
per ocean or air freight quote, down from one to three days
Hundreds of in-house AI agents embedded across the shipment lifecycle (quoting, orders, appointments, missed-pickup checks) and now ocean and air quoting, ocean booking and customs brokerage, built and run under a lean waste-removal discipline by 450+ in-house engineers and data scientists (source).