Optimising Temporary Accommodation Placement Across London with AI-Powered SaaS in E-Governance Systems
2026-06-15 • Computers and Society
Computers and SocietyArtificial IntelligenceSocial and Information Networks
AI summaryⓘ
The authors describe DOMUS, a cloud-based AI tool developed to help London local authorities find temporary housing for people in need more quickly and fairly. It combines rules about housing needs, costs, and location with AI to rank options while still letting staff make final decisions. Testing in Newham showed it saves time, follows rules better, and is liked by staff. The authors suggest it could be used in other government areas where rules and limited resources matter. Their work shows AI can be carefully and ethically used to help local government services.
temporary accommodationAI decision support systemLondon Borough of Newhampolicy constraintslarge language modelsaffordability thresholdspublic administrationcloud computingrule-based filtering
Authors
Hankun He, Jordan Richards, Gopalakrishnan Netuveli, Kumar Aniket, Ramya Pachatcharam, Binta Ade-olusile, Nathan Nagaiah, Matthew I Bellgard
Abstract
Temporary accommodation has become a major fiscal and administrative pressure for English local authorities, particularly in London, where demand and costs have risen sharply. This paper documents the creation and use of DOMUS, a cloud-based, AI-enabled decision-support system built from scratch at the University of East London and customised for the needs of London Borough of Newham to support statutory Temporary accommodation placement. DOMUS integrates household case records, policy-constrained affordability and suitability rules, and live private-rental listings within a single governance-aligned workflow. The system combines transparent, rule-based filtering with large language model-assisted search to standardise the application of bedroom need, affordability thresholds, geographic preferences, and accessibility requirements, while preserving officer discretion and audibility. Household and property attributes are encoded into policy-consistent representations prior to AI-assisted ranking and explanation. A pilot deployment in Newham's secure environment evaluated operational performance relative to manual workflows. Results indicate substantial reductions in search time, improved adherence to key placement constraints, and high staff satisfaction, while maintaining statutory compliance and role-based accountability. Beyond TA, the paper frames DOMUS as replicable digital public infrastructure: a modular, cloud-native Software-as-a-Service architecture that can be deployed across other UK boroughs and adapted to other public administration tasks characterised by scarcity, rule-bound eligibility, and high stakes. The findings demonstrate the feasibility of scalable, ethically governed AI deployment in local government and contribute to debates on AI-enabled public value creation in e-governance.