The Web-Change Assurance and Proof-of-Repair Platform.
PatchProof AI detects issues, maps their business impact, generates safe AI-driven repairs, validates critical customer journeys and produces auditable evidence — so every website change ships with confidence.
- £360M–£1.2B
- UK TAM (annual)
- 43%
- UK businesses hit by a breach (past 12 months)
- £100–£325
- SME website downtime cost per minute
Client site · Checkout journey · Ref PPR-2026-00184
From detection to auditable proof — in a single workflow.
Existing tools stop at detection. PatchProof AI manages the complete lifecycle: detect, understand, repair, simulate, validate and prove.
Detect issues
Continuous monitoring surfaces anomalies, script changes and regressions across the website ecosystem.
Map dependencies
The Web Change Assurance Graph links CMS, APIs, third-party scripts and infrastructure to business outcomes.
Generate a repair
The AI Repair Engine produces a structured plan: root cause, impact, actions, validation and rollback.
Score the risk
A proprietary safety framework decides whether a change auto-applies, needs approval, or is blocked.
Simulate & preview
Patch Preview simulates the change across infrastructure, scripts and integrations before deployment.
Validate journeys
End-to-end tests confirm checkout, payments, forms, bookings and consent still work.
Prove the result
A Proof-of-Repair Evidence Report captures every step, validation and rollback option.
Website change is fragmented, un-governed, and quietly costing revenue.
Modern organisations rely on websites for revenue and service delivery, yet the tooling around them is a collection of disconnected point solutions. Businesses are left to manually bridge the gap between detection, impact, repair, validation and evidence.
- Fragmented tooling: scanners, visual regression, uptime and CMS plugins operating in silos.
- No dependency awareness — scripts, APIs and third parties impact revenue in ways no tool maps.
- Weak repair workflows: generic suggestions, no root cause, no rollback plan, no governance.
- Traditional monitors watch uptime while checkout, forms and consent silently fail.
- No auditable evidence that a repair actually worked and did not create side effects.
Small technical changes reach production before their business impact is understood.
A new software category: Web Change Assurance.
PatchProof AI combines dependency intelligence, AI-driven remediation, risk-bounded automation, customer-journey validation and evidence-based governance in a single platform.
Website Digital Twin
A live, structural replica of the website — its components, content, configuration and integrations — kept continuously in sync so every change can be understood before it ships.
Web Change Assurance Graph
A dependency model connecting CMS, themes, APIs, DNS, CDN, analytics and consent platforms to the revenue-critical business journeys they support.
AI Repair Engine
Context-aware, structured repair plans with root-cause analysis, impact assessment, recommended actions, validation requirements and rollback procedures.
Energy-Based Safety Model
A proprietary energy-based framework scores repair confidence, dependency exposure and business impact — automating only what is provably safe.
Business Journey Validation
Validates what actually matters to the business: checkout, payments, lead forms, bookings, registrations, donations and consent — end to end.
Proof-of-Repair Evidence Ledger
A permanent, auditable ledger of every discovery, repair, approval, validation and rollback — ready for clients, auditors and insurers.
Five ways PatchProof AI protects revenue and trust.
Web agency managing 80 WordPress sites
Pre-update dependency scans, Patch Preview and post-update visual, functional and journey validation — replacing manual QA across a maintenance portfolio and producing client-ready Proof-of-Repair reports.
E-commerce store protecting checkout
Continuous monitoring detects a changed third-party payment script, the Assurance Graph maps its impact, the Repair Engine proposes a fix and the platform validates the full transaction flow before revenue is lost.
Private clinic restoring lead generation
SMTP, SPF, DKIM and DMARC misconfiguration analysed alongside the contact form. A controlled repair with test enquiry restores the primary patient-enquiry channel — with delivery evidence attached.
Charity safeguarding a donation campaign
Digital baseline before launch, continuous change scoring during the campaign, end-to-end donation journey testing and governance-ready evidence packs for trustees and funders.
SaaS company launching a product
Baseline capture, dependency analysis on updated landing pages and CRM integrations, then automated validation of demo requests, notifications, metadata and journey continuity — a Proof-of-Release Report closes the loop.
Dependency-aware AI, governed by a proprietary safety framework.
A continuously generated Web Change Assurance Graph feeds context-aware AI repair generation, risk-bounded automation, infrastructure simulation, business-journey validation and a Proof-of-Repair Evidence Ledger.
- APIs & CI/CD pipeline integration
- Ticketing and approval workflows
- Role-based access controls
- Multi-site management dashboards
One report. Every action, validated and evidenced.
Every remediation cycle produces a comprehensive evidence package: validation results, change history, dependency analysis, test outcomes, automated logs and a human-readable summary — suitable for clients, auditors and insurance.
- Website
- Client production site · Checkout journey
- Change summary
- Payment script update + consent tag reconfiguration
- Dependency scope
- CMS · Payment gateway · Analytics · Consent manager
- Safety score
- Auto-apply threshold met · 96 / 100
- Approval record
- Reviewed & approved by senior engineer · 09 Jul 2026
- Rollback status
- One-click rollback plan attached · verified reversible
- Before & after screenshots
- Homepage · Checkout · Confirmation captured
- Before & after scan results
- Security, performance & accessibility diffed
- Validation tests
- 34 journey assertions executed · 34 passing
- Journey validation
- Checkout · Payment · Confirmation · Lead form — all passing
- Reviewer
- Signed off · full audit trail retained in evidence ledger
A large, underserved UK market for website assurance.
Bottom-up SaaS sizing across UK agencies, digitally dependent SMEs, e-commerce, compliance-sensitive organisations and multi-site operators. Average annual contract value: £1,200–£2,400.
Five segments served by the same assurance platform.
Why PatchProof AI?
Visual regression tools, security scanners, uptime monitors and CMS maintenance plugins each cover a fragment of the problem. PatchProof AI is the operational assurance layer that connects them all — from detection to validated, evidenced repair.
From MVP pilots to a scaling UK SaaS.
Build & Validate
Company setup, capitalised MVP build, core Assurance workflow (detection, dependency mapping, AI repair, patch preview, journey validation, evidence). Paid pilots with agencies begin M7.
Commercial Launch
Transition pilots to recurring SaaS. Launch commercial pricing. Expand from agencies into SMEs, e-commerce and digital service providers. Introduce integrations, reporting and channel partnerships.
Scale & Expansion
Enter compliance-sensitive sectors: healthcare, education, charities and regulated SMEs. Target multi-site organisations. Enhance AI repair, safety scoring and validation coverage.
| Year | Theme | Customers | Revenue Target |
|---|---|---|---|
| Year 1 | MVP development, validation & paid pilots | 5–10 pilots | £34,000 |
| Year 2 | Commercial launch & recurring growth | ~150 | £301,000 |
| Year 3 | Scale, compliance sectors & multi-site | ~260 | £732,000 |
Targets from the PatchProof AI three-year plan. Actual outcomes depend on market conditions, sales execution and customer adoption.
Moin Ahmed
Founder & Product Lead · United Kingdom
- Data Analyst — Unique Solutions (Tableau, SQL, BI)
- IT Support Specialist — Spectrum Solutions (JIRA, Azure)
- Customer Support Executive — Ibex
- Freelance Software Developer — 2024–present
The original contribution behind PatchProof AI.
PatchProof AI originated from Moin Ahmed's direct observation, through technical support, data analysis and software development work, that businesses use multiple disconnected tools to monitor websites — but none manage the complete lifecycle from detection to validated, evidenced repair.
He conceived the Web Change Assurance Graph — linking website infrastructure, software components, third-party services and business-critical functions through a dynamic dependency model — and specified the platform's core design across the detection engine, AI repair engine, safety scoring, patch preview, validation framework and Proof-of-Repair Evidence Ledger.
He also defined the commercial strategy: the initial agency beachhead, phased expansion into SMEs, e-commerce, compliance-sensitive sectors and multi-site enterprises, and the pricing, pilot and customer acquisition model.
Stop shipping website changes without proof.
PatchProof AI is onboarding a founding cohort of UK web agencies and digital maintenance providers into paid pilots. Bring your next planned change — leave with a validated, evidenced repair.