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Housing

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Client: Stonewater

Tenant Support Automation for a UK Housing Association

Implemented AI-assisted tenant enquiry handling and repairs triage to improve response speed and service consistency.

Public ServicesTenant SupportWorkflow Automation

Project Snapshot

Live delivery proof

-33%

First-response time

+21%

Resolution consistency

-27%

Manual triage effort

Client: Stonewater

Date: 17 Apr 2025

Engagement: Service operations transformation

Duration: 12 weeks

Delivery Team: 1 programme lead, 1 workflow specialist, 1 data engineer, 1 service quality analyst

Process Automation & RPANatural Language Processing & ChatbotsAI Training & Workshops

Challenge

High inbound volume and manual triage workflows were creating long response times and uneven tenant experience.

Approach

We built a structured enquiry triage model with repairs categorisation, urgency scoring, and escalation pathways for vulnerable tenants.

Impact

Service teams reduced queue pressure while improving decision quality and transparency across tenant support operations.

Implementation Narrative

Detailed delivery breakdown for Stonewater.

Business Context

The organisation managed repairs, tenancy support, and community service enquiries across multiple regions. Contact volumes were high and often included incomplete information, making effective triage difficult.

Core Challenges

  1. Inconsistent categorisation of inbound tenant enquiries.
  2. Delays in routing urgent and vulnerable-tenant issues.
  3. Limited service visibility for team leaders and managers.

Delivery Approach

  1. Tenant enquiry classification and urgency support rules.
  2. Repairs triage automation with category and priority logic.
  3. Escalation and audit trail controls for sensitive cases.

Implementation Timeline

  • Weeks 1-3: Service process analysis and triage criteria definition.
  • Weeks 4-7: Workflow build, integration, and quality controls.
  • Weeks 8-10: Pilot in selected regions and escalation testing.
  • Weeks 11-12: Full rollout and team enablement.

Operational Outcomes

Service leaders gained a clearer, data-driven view of support workload and escalation pathways. Staff handled more volume without compromising safeguarding and quality processes.

Next-Phase Roadmap

Future scope includes self-service appointment flows and predictive repairs demand planning.

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