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AI Cleanliness
Audit Workflows

Make cleaning measurable from assignment to approval. The platform coordinates photo capture, AI verification, decision rules, rework and audit-ready reporting in one complete workflow.

Mobile and web
No additional hardware
Audit-ready evidence
Clean shared workspace verified through a Cleensight audit workflow
Workflow result
Completed
Audit passed
12 checks verified · photo evidence recorded
How it works

Turn every clean into a verified workflow.

Assign inspections, capture evidence, verify results with Vision Agents and automatically trigger the next operational action.

01

Assign

Assign a workflow to a team, site or individual.

02

Capture

Complete the inspection using the mobile or web app.

03

Verify

The Cleanliness Evaluator scores visible cleaning quality, while the optional Visual Verification Agent confirms required items, room setup or reference standards.

04

Decide

Apply your rules to determine the outcome automatically.

05

Notify

Route exceptions to the right people for action.

06

Report

Generate a complete audit trail with evidence and results.

Powered by Tiliter Vision Agents

The visual intelligence behind every audit

Cleensight combines specialised Vision Agents inside one operational workflow, so each inspection can evaluate cleanliness and verify the standards that matter.

Visual Verification Agent

Automatically verifies required items, equipment, room setup and operational requirements from images by comparing them against expected standards.

Explore the Visual Verification Agent →
Additional Vision Agents can be added to verify damage, inventory, PPE, documentation and other operational requirements.
Built for real operations

Cleaning verification at scale

Apply consistent standards across teams, locations and contracts without adding complex equipment or manual reporting.

Commercial cleaning staff working in a university building

Commercial Cleaning

Prove completed work, standardise quality checks and give clients reliable evidence across every contract.

Retail store maintained through a cleanliness verification workflow

Retail and Supermarkets

Maintain consistent standards across stores, departments and high-traffic customer areas.

Hotel room checked through a mobile cleanliness audit

Hotels and Hospitality

Verify rooms, bathrooms and shared areas before they are released to guests.

Audit-ready reporting

Every completed workflow creates a trusted record

The platform brings the photos, verification results, exceptions and follow-up actions together in one structured report.

Complete audit trail

Record time-stamped images, verification results, user activity and follow-up actions.

Consistent standards

Apply the same audit criteria across every site, team and reporting period.

Actionable exceptions

Identify issues, document rework and highlight what still requires attention.

Operational insights

Compare performance across locations, contracts, teams and time periods.

Cleanliness Audit Report
ABC Hospital · Ward A
14 February 2026 · 20:42
Completed
3
Overall result
Rework recommended
Issues detected
2 flagged
Follow-up required
Evidence
12 photos
Time-stamped
Area results
Patient bathroom
Needs rework · 2/5
Nurse station
Very good · 4/5
Corridor
Very good · 4/5
Patient bathroom · Needs rework
20:39
Bathroom image flagged for cleaning rework
A missed detail was detected on a high-touch surface. The item was flagged for rework based on the workflow criteria.
⚠ High-touch surface issue · rework triggered
Estimate the operational value of AI-powered cleanliness audits.
AI-powered cleanliness audits help reduce manual QA effort by turning inspection photos into structured, reviewable results.
Number of cleaners 1,200
AI-scored photos per cleaner per day 8
Working days per year 250
QA time saved per AI-scored photo (sec) 20 sec
QA / management hourly rate ($) $20
Current rework rate (%) 3%
Reduction in rework incidents (%) 20%
Avg rework cost per incident ($) $40
QA labour saved / year
$3M
Estimated review time recovered
Rework savings / year
$216k
Estimated reduction in repeat work
Estimated annual value
$3.2M
Value-to-cost: 7.5×
QA labour savings$3M
Rework savings$216k
Illustrative annual software cost$432k
This cost line is indicative only and intended to help compare estimated operational value against a realistic rollout threshold.

At 8 AI-scored photos per cleaner per day across 1,200 cleaners over 250 working days, AI-powered cleanliness audits can generate an estimated annual value through reduced QA effort and lower rework.

This calculator estimates annual value using cleaner count, AI-scored photos per cleaner per day, working days, time saved in review or QA handling per image, baseline rework rate, the assumed reduction in rework incidents, and the average cost of each rework event.

Most organisations start with a defined scope, validate the operational impact, and then expand based on measured results.


Focused deployments first
Many teams begin with selected sites, inspections, or QA workflows rather than a full operational rollout from day one.
Expansion based on proven value
Broader rollout decisions are typically based on measured impact, including time saved, stronger auditability, and reduced manual review effort.
How is ROI typically created?
The strongest drivers are usually reduced manual QA effort, more consistent scoring, reduced repeat work, and better auditability across sites.
How is software cost estimated here?
The cost estimate is based directly on AI-scored image volume. Cleaner count, AI-scored photos per cleaner per day, and working days are used to estimate annual image volume, then mapped to an indicative enterprise rollout assumption.
Why use images as the pricing driver?
The pricing is ultimately tied to AI-scored image volume. This makes the calculator easier to understand and ensures software cost increases when image activity increases.
What if we do not have supervisors reviewing every photo?
That is common in larger operations. In those cases, the software’s value often shifts from sampled manual review toward broader visibility across after photos, helping teams catch more issues and reduce repeat work.
Can this start with a limited rollout?
Yes. Many deployments begin with a small number of sites or a defined QA workflow before expanding more broadly.
How should these numbers be interpreted?
These figures are indicative only and based on the assumptions selected above. Actual results depend on workflow design, inspection frequency, labour rates, rework patterns, image volume, and rollout scope.