AI Governance

AI Risk Management Report

House Made Ready Limited

Version

1.0

Date

September 2026

Prepared By

Luke Roberts (Founder & CEO)

Classification

Confidential

Governance Standard

UK DSIT AI Risk Management Toolkit & HM Treasury Orange Book Framework

1.0

Executive Summary & Scope

House Made Ready Limited ("House Made Ready") is a UK-based property intelligence platform that integrates real-time planning data, including Permitted Development Rights (PDR), Article 4 directions, and Conservation Area constraints, with HM Land Registry price-paid records and broader property datasets. The platform automatically generates 60-second property scorecards and data cards that power its proprietary AI engine, Maggie AI, to produce automated, accurate architectural insight packs, financial ROI projections, Strategic Staging Reports, Investment & Mortgage insight packs, development feasibility studies, and real-time conversation for B2C and B2B users.

This report establishes House Made Ready's formal AI Risk Management Framework in alignment with the UK Department for Science, Innovation and Technology (DSIT) AI Risk Management Toolkit. It defines the governance structures, systematic risk assessments, mitigation controls, and continuous audit protocols necessary to manage operational, legal, technical, and ethical risks across all active and pipeline AI capabilities.

1.1

In-Scope AI Systems & Technical Stack

Maggie AI Core Intelligence Engine & Data Card Framework

Proprietary AI engine that ingests real-time HM Land Registry price-paid data, Local Planning Authority (LPA) portals (PDR, Article 4 directions, Conservation Areas), and geospatial mapping to build structured property data cards. These cards drive the automated generation of:

  • • Instant 60-second Property Scorecards & Feasibility Studies
  • • Architectural Insight Packs
  • • Financial ROI Projections
  • • Investment & Mortgage Insight Packs
  • • Strategic Staging Reports

Estate Agent Marketing Suite

Automated content generation engine utilising OpenAI GPT-6 to craft property descriptions, social media collateral, portal listing optimisation, and buyer communication templates.

Professional & Trade Matching Logic

Algorithmic matching system that pairs high-intent homeowners and developers with verified architects, surveyors, and builders based on geographic data, property constraints, and project scope.

Generative Staging & Visual Design Engine

Generative image modelling (integrating tools such as DALL-E / Midjourney) to produce automated visual staging overlays and preliminary design concepts for Strategic Staging Reports.

Inbound Conversational AI (Voice & Text)

Automated conversational agents for scaling incoming customer inquiries, onboarding estate agents, SME property developers and homeowner leads, and assisting initial property triage.

2.0

Governance & Ownership Structure

House Made Ready adopts a multidisciplinary governance approach to ensure comprehensive oversight across technical performance, legal and regulatory compliance, data privacy, and commercial operations.

Executive Lead & AI Officer

Luke Roberts (Founder & CEO)

Ultimate accountability for overall AI risk appetite, sign-off on high-risk model deployments (including core updates to Maggie AI), and enforcement of emergency system suspension protocols.

Commercial & Partner Lead

Jacqueline Butler (Commercial Growth Lead)

Oversight of B2C homeowner privacy data & B2B estate agent, developer, and trade network data compliance, collection and routing of user feedback loops, and validation of AI-generated marketing and sales output accuracy.

Technical & Data Pipeline Lead

Lead Architect / Technical Partner

Oversight of data ingestion security across HM Land Registry and Local Planning Authority (LPA) APIs, real-time data card generation integrity, API rate-limiting, Maggie AI algorithm drift monitoring, and prompt engineering guardrails.

Legal & Compliance Advisor

External Counsel / DPO

Safeguarding UK GDPR compliance, conducting copyright/IP risk reviews for AI-generated outputs, reviewing third-party AI vendor SLAs/DPAs, and maintaining alignment with ICO and DSIT guidelines.

3.0

Comprehensive AI Risk Matrix

Risks are categorised according to the four core pillars of the UK GOV.UK AI Risk Management Toolkit: Legal & Regulatory Compliance; Technical Robustness & Data Quality; Fairness, Bias & Societal Impact; and Accountability, Redress & Remediation.

R-01Legal & Data PrivacyHigh

Third-Party LLM Data Leakage: Users or estate agents inputting PII or confidential seller details into GPT-4-powered tools, exposing data to model retraining without Enterprise Data Protection Agreements (DPAs).

Likelihood: MediumImpact: High
R-02Technical RobustnessHigh

Maggie AI Planning & Feasibility Hallucination: Maggie AI misinterpreting LPA datasets (PDR, Article 4 directions, Conservation Area boundaries), resulting in inaccurate Property Data Cards and flawed Architectural Insight Packs.

Likelihood: MediumImpact: High
R-03Technical RobustnessMedium

Financial & Mortgage Data Drift: Stale HM Land Registry price-paid data or flawed API calls causing Maggie AI to output inaccurate ROI projections or misleading Investment & Mortgage Insight Packs.

Likelihood: MediumImpact: Medium
R-04Legal & IPMedium

Generative Visual & Content Infringement: Generative design tools (DALL-E/Midjourney) or automated copy engines producing copyrighted imagery or deceptive representations in Strategic Staging Reports.

Likelihood: LowImpact: Medium
R-05Fairness & BiasMedium

Algorithmic Trade & Professional Referral Bias: The matching engine systematically favours specific architects, surveyors, or builders due to skewed review weighting or postcode demographic factors.

Likelihood: LowImpact: Medium
R-06AccountabilityMedium

Unvetted Voice/Text AI Customer Binding: Conversational agents hallucinating pricing, quoting incorrect fee structures, or making unauthorised contractual commitments to B2B or B2C users.

Likelihood: LowImpact: High
4.0

Risk Treatment, Mitigations & Action Plan

R-01: Data Privacy & Third-Party LLM Security

  • • Enterprise DPAs: Enforce strict zero-data-retention agreements with LLM API vendors, explicitly prohibiting use of customer inputs for base model retraining.
  • • Client-Side PII Sanitisation Engine: Deploy automated data scrubbers to strip PII before data reaches external LLM prompts.
  • • UK GDPR Compliance: Ensure all data flows comply with UK ICO AI Guidance, maintaining clear lawful bases for processing personal property records.

R-02: Maggie AI Planning Guidance Hallucinations & PDR Errors

  • • Human-in-the-Loop (HITL) Audit Workflows: Mandatory review by a qualified architectural practitioner for all premium outputs before customer dispatch.
  • • Prominent Informational Disclaimers: Embed clear legal disclaimers on free scorecards establishing that Property Data Cards present indicative planning appraisals, not statutory planning decisions.
  • • Automated Boundary Verification: Cross-check Maggie AI's PDR assessment logic against live LPA spatial datasets.

R-03 & R-05: Financial Valuation Drift & Data Pipeline Accuracy

  • • Dual-Engine Valuation Verification: Cross-reference automated ROI projections against street-level HM Land Registry price-paid API feeds.
  • • Pipeline Health Telemetry: Automated weekly validity checks and anomaly alerts on local planning portal API connections.

R-04: Generative Staging & Visual/Content IP Safeguards

  • • IP & Copyright Filtering: Audit generative visual algorithms to ensure output images do not infringe on third-party design copyrights.
  • • Watermarking & Disclosure: Clearly label all AI-generated architectural overlays, conceptual floor plans, and staging visualisations as "AI-Generated Illustrative Concepts".

R-05: Algorithmic Trade & Professional Referral Bias

  • • Objective Matching Framework: Base trade and professional matching purely on deterministic factors: verified insurance, professional accreditations, geographic proximity, and verified user ratings.
  • • Quarterly Bias & Allocation Audits: Conduct quarterly statistical reviews of lead allocations to ensure equitable distribution across contractors.

R-06: Automated Voice & Customer Interaction Safeguards

  • • Strict Operational Boundary Controls: Apply tight system instructions and prompt guardrails to inbound conversational AI agents.
  • • Prohibition of Binding Commitments: Programmatically block voice and chat AI systems from issuing legally binding quotes, executing contract agreements, or giving formal legal advice without CEO sign-off.
5.0

Third-Party Vendor Due Diligence Framework

House Made Ready enforces a strict vendor vetting procedure before integrating external APIs, LLMs, voice agents, or spatial data feeds. This framework ensures all third-party integrations comply with UK DSIT standards and UK GDPR requirements.

Data Privacy & Retention

Vendor must contractually guarantee zero data retention for training purposes. Must support UK/EU data residency where applicable.

Verification: Review API Terms of Service, Enterprise DPA, and Data Transfer Assessments.

System Reliability & SLA

Vendor must guarantee operational uptime and sub-second API latency response times to maintain the 60-second scorecard delivery commitment.

Verification: Status page monitoring & SLA agreement.

Cybersecurity Standards

Mandatory SOC 2 Type II or ISO/IEC 27001 certification. End-to-end encryption required for all property records and PII (TLS 1.3 in transit, AES-256 at rest).

Verification: Security compliance documentation review.

Model Explainability

AI model providers must furnish comprehensive system documentation detailing dataset provenance, known hallucination rates, safety alignment filters, and prompt injection defences.

Verification: Technical model cards & system documentation.

Operational & Financial Resilience

API providers must maintain clear deprecation policies (minimum 6 months advance notice) and demonstrate operational stability.

Verification: Review developer documentation, vendor roadmap disclosures, and financial health assessments.

6.0

Continuous Monitoring, Audit & Incident Response

House Made Ready operates a three-tiered continuous monitoring and auditing framework to ensure Maggie AI, property data card generation pipelines, and third-party API dependencies maintain high levels of accuracy, safety, and legal compliance.

Tier 1: Real-Time Automated Logging & Telemetry

  • • API & Model Performance: Continuous telemetry monitoring of token consumption, API response latency, and failure rates across HM Land Registry and LPA endpoints.
  • • Guardrail & Prompt Failure Tracking: Automated logging of prompt injection attempts, guardrail blocks, data sanitisation triggers, and zero-data-retention API flag status.
  • • Data Card Output Validation: Automated pre-rendering checks that flag unexpected numerical variances or missing constraint data before outputs reach end users.

Tier 2: Monthly Human QA & Deliverable Sampling

  • • 5% Qualitative Sample Audit: Monthly review of 5% of all AI-generated outputs for factual accuracy, tone, and compliance.
  • • Maggie AI Feasibility Spot-Checks: Dedicated review comparing Maggie AI's automated Property Data Cards against statutory planning registers.
  • • User Feedback & Dispute Loop: Aggregation and review of user-flagged inaccuracies submitted via platform feedback channels.

Tier 3: Quarterly Governance & Regulatory Review

  • • Formal Executive Sign-Off: Quarterly review led by the Founder & CEO and Commercial Growth Lead to reassess the AI Risk Register.
  • • Vendor Risk Re-Assessment: Re-evaluating third-party DPAs, SOC 2 compliance certificates, and SLA performance across all integrated API vendors.
6.2

AI Incident Response & Escalation Protocol

In the event of a critical failure, House Made Ready initiates a 3-step escalation protocol:

Step 1: Containment & System Fallback (Immediate)

  • • Instantly trigger system fallback protocols, isolating the affected AI tool or model endpoint.
  • • Switch standard report generation to static, rule-based architectural logic feeds to maintain platform availability.
  • • Temporarily suspend customer-facing conversational agents if unauthorised commitments or pricing errors are detected.

Step 2: Diagnostic Investigation (Within 2 Hours)

  • • Isolate technical telemetry and system logs to identify the root cause (e.g., prompt injection, corrupted API data, or model update drift).
  • • Evaluate the blast radius to identify all users who received impacted Property Data Cards or insight packs.

Step 3: Remediation, Statutory Reporting & Model Update

  • • Regulatory Notification: If PII is compromised, execute formal breach reporting to the UK ICO within the statutory 72-hour UK GDPR window.
  • • Client Communication: Re-issue corrected Property Data Cards or Architectural Insight Packs to impacted clients with full disclosure.
  • • System Mitigation: Patch prompt guardrails, update logic scripts, or re-engineer Maggie AI parameters before restoring full AI service.

Report Sign-Off & Approval

Approved By: Luke Roberts, Founder & CEO, House Made Ready Limited

Next Review Date: December 2026

End of Report

Contact

Company

House Made Ready Limited

Co. No: 16933702

© 2026 House Made Ready™ Limited. All rights reserved.