Washmen achieves 90% faster claim resolution with Asana • Asana

Washmen achieves 90% faster claim resolution with an automated AI production loop

Washmen, the UAE’s leading tech-driven textile care service, revolutionized its luxury garment operations by building a self-running quality and claims system in Asana. By deploying Asana AI Teammates and AI Studio, Washmen transitioned from manual, memory-based processes to a connected chain of AI agents that pass work to one another automatically. This transformation reduced average claim resolution time from three days to just six hours and allowed the business to scale without increasing administrative headcount.

Subjective decision-making

Inconsistent human assessments of delicate fabrics led to avoidable damage incidents on high-value items.

No institutional memory

Past damage history lived in individual memories, leading to repeated errors on similar fabric and brand combinations.

Linear headcount dependency

Every increase in order volume required more hiring, making expansion operationally expensive and difficult to scale.

Connected AI production loop

A chain of four Asana AI Teammates operates in sequence to manage valuation, quality control, risk screening, and compensation without human intervention.

Physical-to-digital sync

A real-time API integration moves Asana task cards automatically based on physical station scans at the facility.

AI-driven risk sentinel

AI cross-references every newly assessed garment against a historical claims database to flag risks before production begins.

90% faster claim resolution

Average resolution time dropped from 2–3 days to just 6 hours.

15 high-risk damage incidents prevented

By the AI Damage Risk Sentinel before items entered production.

40–50% reduction in manual work

Across operations by eliminating repetitive data entry and coordination.

Scale-proof growth

Each active AI Teammate delivers the output equivalent of approximately one full-time employee.

Winner: 2026 AI Breakthrough Award, EMEA

Recognized for pioneering a connected chain of autonomous AI agents, Washmen has established a global benchmark for AI-augmented physical operations. By embedding AI into the logic of a legacy service industry, Washmen has successfully shifted from reactive damage fixing to predictive risk prevention.

As an Asana Implementation Partner, Cloudfresh was the primary architect of Washmen's move to a high-scale, AI-powered operations hub. They translated Washmen’s complex facility needs into practical AI workflows—facilitating the transition to Asana Enterprise and conducting the operational workshops that turned manual task management into a fully autonomous system.

AI Studio and AI Teammates has transformed how we collaborate, turning complex workflows into intelligent, automated actions and allowing our teams to focus on delivering an unparalleled experience to our customers.
Jad Halaoui, Co-founder & COO, Washmen

Stage 1: Automated intake and real-time operational sync

Previously, tracking 250+ ShoeCare items daily required manual data entry, leading to outdated information and mismatches between the facility floor and digital records. Washmen and Cloudfresh built a real-time bridge using the Asana API to connect physical facility stations directly to digital boards.

Zero-entry intake: When an item enters the pipeline, the system automatically creates a fully populated task card with brand, size, and customer instructions.
Physical scan to board move: When a team member scans an item at a facility station (e.g., pressing or QC), the corresponding Asana card moves automatically to that station’s column.
Automatic documentation: Before-and-after photos captured on the floor are automatically attached to tasks, ensuring consistent evidence for 7,500+ tasks monthly.
Live data sync: Any backend order updates refresh the Asana card description in real time, ensuring teams never work from outdated information.

The most transformative element is the physical scan driving a live Asana board column. A team member scans an item at a station, and the task card moves. This replaces an entire layer of manual coordination and transforms Asana into a live operational map of the building.”
Andrew Villamor, Operations Associate, Washmen

Stage 2: Foundation and preventive risk screening

In luxury garment care, one mistake on a high-value piece can cost thousands of dirhams. Washmen deployed a connected chain of Asana AI Teammates to act as a predictive safety net, identifying risks before a garment is even processed.

Automated valuation assistant: An AI Teammate researches current retail values from UAE and international luxury retailers to set the risk threshold for every item.
AI QC validator: This teammate reviews care plans against six risk categories (e.g., color bleeding, texture change) and brand-specific sensitivities within two minutes of assessment.
Damage risk sentinel: AI Teammates cross-references item attributes against Washmen’s full historical claims database, flagging fabric combinations that have gone wrong before.
Automatic escalation: If a high-value item has a risky care plan, AI Teammates raise a structured alert, preventing production from starting until a human reviews the risk.

We went from quality checks living in people's heads to a system where institutional knowledge is applied to every single item. An item gets assessed, and within two minutes, four layers of quality control run in parallel, triggered automatically by a connected loop of AI Teammates.
Andrew Villamor, Operations Associate, Washmen

Stage 3: Autonomous compensation and claim resolution

Claim handling traditionally required agents to spend 2–3 days manually researching item prices and customer history. Washmen now utilizes a Compensation Evaluator AI Teammate to produce a complete 9-section report, allowing the customer experience team to resolve issues in minutes rather than days.

Sourced valuation anchors: An AI Teammate researches item values from verified retailer URLs to anchor compensation to current pricing, eliminating guesswork.
Customer value awareness: The report factors in customer lifetime value and order history so high-value clients receive appropriately considered outcomes.
Drafted customer messages: An AI Teammate generates a professional, empathetic message with the compensation offer, which agents can review and send immediately.
Strategic visibility: Management dashboards aggregate claim trends and risk flags in real time, shifting the focus from fixing mistakes to preventing them entirely.

Conclusion

By building an automated AI production loop in Asana with Cloudfresh, Washmen has decoupled its growth from payroll, allowing it to scale across the UAE without sacrificing its premium service standard. The transformation has turned Asana into a digital backbone that connects physical facility scans to intelligent, data-backed decisions. As Washmen moves toward predictive risk modeling, its AI-augmented operating model ensures that the UAE’s most valuable garments are handled with absolute precision and documented care.

It’s been incredible seeing Asana’s impact on Washmen’s operations. As one of the first organizations in EMEA to adopt Asana AI Teammates, they quickly moved from structured task management to a true human-agent operating model—autonomously resolving 25,000 damage claims a day. That’s what successful implementation looks like.
Norbert Durko, General Manager for the Middle East at Cloudfresh