InspectIQ — AI Home Inspection App

Overview

InspectIQ is an AI-assisted home inspection app that we designed and built as a product for maintenance professionals and inspection teams. An inspector walks a property with an iPhone or iPad, works through a structured checklist, and attaches photographs to the exact items they support. The app is native iOS in SwiftUI, with Core ML for on-device intelligence and Firebase for shared storage.

The Challenge

Property inspections depend on the person doing them. One inspector remembers the consumer unit and the loft hatch; another does not. Photos land in a camera roll, and by report time nobody is sure which picture showed which fault. For a company sending several staff to different properties, that variation weakens reports and makes quality hard to audit. On site there is also a practical constraint: basements, plant rooms and rural properties often have weak signal, so a tool needing a live connection fails at the worst moment.

Who Uses It and How

Field inspectors are the primary users. They open the assigned property and the checklist appears section by section. They mark an item satisfactory, defective or not accessible, add a note and take photos without leaving that item. One-handed use and bright sunlight shaped the controls.

Team leads and office staff review completed inspections afterwards, see photographs beside the finding they support and spot skipped items.

Our Approach

The checklist is the spine. Every inspection is a template of sections and items, so coverage is decided by the business, not by whoever holds the phone. Photos belong to items rather than floating free. We then asked where machine learning genuinely helps a busy person, and kept it assistive: it proposes, the inspector decides.

What We Built

Each inspection opens with a property summary and a progress view showing sections completed and items outstanding. Within an item, the inspector records a status, adds notes and captures photos, which are stored against the item and can be annotated or replaced. Core ML runs on the device to support the AI-assisted side of the workflow, for example helping classify what a photo shows so the inspector has less to type. Completed inspections are saved and available to the wider team, and the design leaves a clear path towards generating written reports from the recorded findings.

Architecture and Data

The data model is straightforward: properties, inspections, sections, items, findings and photos, each linked to its parent. Because connectivity on site is unreliable, work is written locally first and synchronised with Firebase when a connection is available, so an inspector is never blocked waiting for the network. Image files go to cloud storage, with references kept in the inspection record. Core ML models are bundled with the app, which means assistance works offline and the images used for suggestions do not need to leave the device.

Security, Privacy and Quality

Inspections produce photographs of the inside of people's homes, sometimes showing belongings, documents or security arrangements. Access is therefore limited to authenticated team members and to the properties assigned to them, and storage rules stop one company's data being visible to another. For quality, we test the checklist logic, verify that photos stay attached to the correct item after offline sync, and try the app in poor light and with interruptions. Model suggestions are always confirmed by a human.

Technology

SwiftUI provides responsive native screens and good camera integration. Core ML runs models directly on Apple hardware without a network. Firebase supplies authentication, a synchronising database and file storage without a bespoke server.

Outcome

InspectIQ gives an inspection business a repeatable process: the same structured checklist for every visit, and photographic evidence connected to each item. Inspectors get a professional field tool, and managers gain more consistent records to review.

Frequently asked questions

How much does it cost to build a home inspection app?

The biggest cost drivers are how customised your checklists must be, whether the app must work fully offline, whether you want report generation or PDF output, and how much machine learning you need. Supporting both phone and tablet, plus an office-side review interface, also adds scope. We usually start with the core checklist and photo flow and then add the rest.

Can an inspection app work without internet access?

Yes, if it is designed for it. The app saves work on the device and synchronises later, which is essential for basements, plant rooms and rural sites. The engineering effort lies in handling conflicts when two people edit the same record.

How does AI help with property inspections?

On-device models can suggest what a photo shows, pre-fill categories and flag missing items, reducing typing on site. They should assist rather than decide, so the inspector confirms every finding.