Optimising Temporary Accommodation Placement Across London with AI-Powered SaaS in E-Governance Systems

2026-06-15

AI Summary

This study addresses the challenges of high costs, surging demand, and administrative burden faced by London local authorities in temporary housing placements. To tackle these issues, the authors propose DOMUS, a cloud-native SaaS-based AI decision support system that uniquely integrates a transparent rule engine with a large language model (LLM). By synthesizing household profiles, policy constraints, and real-time rental market data, DOMUS enables rule-driven property filtering augmented by LLM-assisted search, standardizing workflows while preserving human discretion. Pilot implementation demonstrates that DOMUS significantly reduces placement search time, enhances policy compliance and staff satisfaction, and ensures statutory accountability with full auditability. The system establishes a reusable, modular paradigm for digital public infrastructure in social housing allocation.

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.

Problem

• Temporary Accommodation
• E-Governance
• Public Housing
• AI in Government
• Resource Allocation

Innovation

• AI-powered SaaS
• e-governance
• temporary accommodation
• large language model
• policy-aware AI