Hennecke Fleet Consulting
AI Vehicle Damage Detection & Automated Vehicle Inspection
What is AI vehicle damage detection?
AI vehicle damage detection means: artificial intelligence analyses images of a vehicle and automatically detects damage such as scratches, dents or rim damage.
The images come either from a permanently installed vehicle scanner or from an app on a smartphone or tablet. Depending on the system, vans, trucks and trailers can be analysed in addition to passenger cars.
This is particularly useful when drivers change frequently – for example in van fleets or in car rental. At every handover, it is documented which damage is new and in which period it occurred. In addition, repair costs can be estimated and the general condition of the vehicle can be documented.
On this page you will find use cases, technology, costs and an overview of providers. Hennecke Fleet Consulting advises you independently – where a commission is involved, we disclose it.
What are AI damage detection and vehicle scanners used for?
In many use cases, AI-based automated damage detection using a vehicle scanner or mobile app makes sense:
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Van fleets and pool vehicles: When drivers change frequently: Which driver caused new damage?
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Damage reporting: In company fleets, the driver photographs damage with a smartphone. The AI identifies the damage.
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Lease returns: Determining which damage counts as normal wear and tear and which damage leads to additional payments.
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Car rental and car sharing: Check-in/check-out at vehicle handover: Is there new damage on the vehicle when the driver returns it?
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Vehicle logistics: When you transport vehicles - When was a vehicle damaged? Who is responsible?
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Used car management: Identifying damage and repair costs that affect the price when buying or selling.
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Insurance: How severe is the damage after an accident or hailstorm? Which damage already exists when underwriting used cars?
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Underbody inspection: In security checks, they are also used to find hidden objects such as explosives.
The value goes beyond the automatic detection of individual damage: The biggest time savings through automation come from automatically comparing the vehicle's current condition with previous ones. A second effect is a falling damage rate, because drivers treat the vehicles more carefully when they know that damage is checked automatically.
How do vehicle scanners and AI damage detection work?
A scanner or an app provides the images, and the AI analyses them: it detects damage, compares it with previous images and estimates the repair costs. Below you can read which hardware is available, what the AI detects and what to look for when choosing a system.
Hardware: Scanner oder App?
Vehicle scanner (portal or tunnel): An enclosed structure with many cameras and its own lighting photographs the vehicle from the side, from above and in some cases also from below as it drives through. Advantages: very high image quality, many vehicles per hour and no effort for the driver. Disadvantages: cost and space requirements of the structure.
Individual fixed cameras: The simpler version of the scanner – cameras are mounted on walls or poles and photograph the vehicle as it enters or leaves. Installation is much simpler and requires less space than a portal – but the cameras inevitably need a certain distance from the vehicle. Both options are suitable when vehicles regularly return to the same location – for example a depot or a rental station.
Mobile solutions (smartphone): Drivers or staff photograph the vehicle with a smartphone or tablet. Advantages: the most flexible option, low hardware costs and usable anywhere. Disadvantage: more manual effort, because someone has to take the pictures. Suitable when vehicles are spread out or handed over at changing locations.
Underbody scanners: A special case – cameras in a drive-over ramp or in the ground photograph the underbody as the vehicle drives over them. They are used for damage detection and in security checks.
Turntable scanners: The vehicle rotates on a platform in front of the camera. The image quality is often not sufficient for damage detection, and the process is usually slow. They are mainly used for remarketing purposes.
Sensors instead of cameras: Some solutions use sensors on the vehicle to measure shocks and vibrations. This makes it possible to detect the location and severity of damage during operation – independently of photos.
What does the AI detect?
Vehicle types: Most systems analyse passenger cars, some also pickups, vans and trucks. For commercial vehicle fleets, this is therefore the first selection criterion. If a scanner is to be used, there is another point: tall vans or trucks must actually fit through it.
Damage: Scratches and dents are standard, and rim damage and broken windows are often detected as well. Some systems also assess the severity – for example whether only the paint is scratched or the damage goes down to the metal. Specialised solutions also capture paint discolouration, panel gap deviations, damage to trailers and bodies, or damage to the interior.
Before-and-after comparison: The greatest benefit comes from automatically comparing the vehicle with previous images. The AI shows which damage has been added since the last handover.
Repair costs: Costs can be estimated in two ways. Either via an API connection to third-party databases such as DAT or GT Motive – this is accurate but incurs additional costs. Or via the provider's own database; the calculation is then less detailed but sufficient for many use cases.
Further detection: Some systems also read the vehicle identification number (VIN), number plate, mileage, tyre tread depth or information from vehicle documents.
How much do vehicle scanners and AI damage detection cost?
The costs of AI solutions for damage detection using vehicle scanners or smartphones depend above all on the chosen technology – and on how many vehicles are inspected and how often. The following overview covers investment costs, costs for the assessment and other influencing factors.
Investment costs
Vehicle scanners: The most elaborate solution – the investment is often more than €50,000 per unit, and considerably more for premium systems. Installation and site costs come on top. Some providers also offer rental or similar financing models for their scanners.
Fixed cameras: Each camera costs a few hundred euros, plus installation and site costs. In total, an installation comes to only just over €10,000. These costs are usually borne by the customer, not the provider.
Mobile solutions: A standard smartphone is all the investment needed.
Costs for the scans
For the actual AI damage detection, there are two common pricing models – for scanners and apps alike:
Price per scan: Usually between €1 and €2 per scan, depending on the type of vehicles, the scope of activities and whether a repair cost estimate or a before-and-after comparison is required. This model suits cases where vehicles are not scanned continuously – for example damage reports or lease returns.
Price per vehicle per month: Includes a fixed number of scans, for example two per day, and usually ranges between €5 and €15 per vehicle per month. This model is particularly suitable for regular scans in commercial vehicle fleets, car rental or car sharing.
Other cost factors
Fleet size: As the number of vehicles increases, the cost per scan usually falls – starting from just a few hundred scans per month. For very large volumes, such as insurers handling millions of claims, prices fall to the marginal cost of AI computing power. Providers differ in whether trailers are counted separately from tractor units.
Additional costs: Ongoing costs may include fees for external repair cost databases such as DAT or gtMotive, or for the internet connection. One-off costs arise for integration into fleet management software or a telematics solution.
Savings: The costs of the scans must always be weighed against the savings from AI damage detection. First, there are time savings from automating damage recording, cost calculation and, above all, the comparison with previous images. Second, there are cost savings because experience shows that drivers cause less damage when damage detection is in use.
Summary: Scanner or app – which pays off? A fixed system tends to pay off when many vehicles regularly return to the same location; if the vehicles are spread out on the road, the app is usually the more economical solution. Whether a system pays off – and which one is recommended – ultimately depends on the number and type of vehicles, the type and frequency of scans and previous damage costs. We will be happy to calculate this for your fleet.
Supplier overview: AI automatic damage detection
Der Markt für KI-Schadenserkennung ist jung und in Bewegung: Neue Anbieter kommen hinzu, andere werden übernommen oder verschwinden wieder vom Markt. Viele Anbieter sind über das Entwicklungsstadium oder einzelne Pilotprojekte nicht hinausgekommen oder liefern keine belastbaren Zahlen zu den Mengen.
Die nachfolgende Übersicht listet die Anbieter neutral und alphabetisch ohne Bewertung oder Rangfolge auf. Aufgeführt sind auch Anbieter, die nur teilweise passen, etwa reine Kalkulationslösungen oder Unterbodenscanner aus dem Bereich Sicherheitstechnik. Mengenangaben stammen von den Anbietern selbst und sind nicht unabhängig geprüft. Die Übersicht ist nicht vollständig und gibt den uns bekannten Stand wieder (Oktober 2026).
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ADI Auto Damage Inspection – Deutschland; Durchfahrtscanner, auch transportabel; Schwerpunkt Versicherung und Hagelschäden
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AFC / CompanionAI – Deutschland; KI-App zur Schadensmeldung mit Kostenschätzung; Schwerpunkt gewerbliche Flotten.
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Autoscan – Deutschland; Durchfahrtscanner für Pkw; Schwerpunkt Autovermietung an Flughäfen, Versicherung und Hagelschäden.
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Checkturio – Deutschland; KI-App für Abfahrtskontrolle; Schwerpunkt Transportunternehmen und Auflieger.
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ClearQuote – Indien; App und fest installierte Kameras; Schadenserkennung und Vorher-Nachher-Vergleich; Lieferflotten, Nutzfahrzeuge, LKW; rund 1,5 Mio. Scans pro Monat.
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Click-Ins – Israel; Web-App mit Smartphone-Fotos und Vorher-Nachher-Vergleich; Schwerpunkt Versicherung, Auktionen, Händler.
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ControlExpert – Deutschland; Software mit KI-Bilderkennung; Schwerpunkt Versicherer und Flotten.
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DAT FastTrackAI – Deutschland; KI-Kalkulation aus Fotos; Schwerpunkt Versicherer, Sachverständige, Werkstätten.
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DeGould – Großbritannien; Scanner-Kabinen am Bandende; Schwerpunkt Autohersteller und Fahrzeuglogistik.
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DEKRA Digital Service – Deutschland; App mit KI-Prüfung; Schwerpunkt Leasingrückgaben; letzte Meldung 2024.
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Fiasco – Deutschland; Plattform für Schadenaufnahme per Smartphone und Reparaturkalkulation; Werkstätten und Versicherer.
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FleetScout – Großbritannien; Kameratürme an Depots plus Fahrer-App; Transporter, Lkw und Auflieger in Logistik und Handel.
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Inspektlabs – USA und Niederlande; App sowie Scanner mit fest installierten Kameras; Schwerpunkt Versicherung, Vermietung, Leasing und Remarketing.
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Instavalo – Deutschland; fest installierter Scanner auf Basis der Tchek-Technik plus App; Schwerpunkt Autohäuser, Leasing und Flotten.
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Macadam – Belgien; App mit KI für Fahrzeugbegutachtungen; Schwerpunkt Leasingende, Vermietung und Carsharing.
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Monk – Frankreich; App und Software-Baustein; Vermietung, Carsharing, Remarketing, Leasingrückgabe und Versicherung.
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MotionsCloud – Deutschland; Browser-App mit KI-Fotoauswertung und Video-Besichtigung; Versicherung und Vermietung.
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ProovStation – Frankreich; Durchfahrtscanner für Pkw, Transporter und Lkw; Schwerpunkt Händler, Vermietung, Logistik; laut Anbieter 28 Mio. Scans insgesamt seit 2020 (Angabe von 2024).
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RavinAI – USA; App und über vorhandene Überwachungskameras; Schwerpunkt Vermietung, Remarketing und Versicherung; laut Anbieter über 1 Mio. inspizierte Fahrzeuge insgesamt (2021).
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Self Inspection – USA; Smartphone-Prüfung per Web-Link mit zusätzlicher Expertenprüfung; Schwerpunkt Autofinanzierer, Leasingrückgabe und Händler; laut Anbieter über 1 Mio. Inspektionen insgesamt.
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Solera Qapter – KI-Kalkulation aus Schadenfotos; Schwerpunkt Werkstätten und Versicherer.
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Tchek – Frankreich; App-Lösung, Scanner über Lizenznehmer Instavalo; Schwerpunkt Händler, Gebrauchtwagen und Vermietung; laut Anbieter über 700.000 Prüfungen und Schätzungen im Jahr 2024.
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Tractable – Großbritannien; Foto-KI und Scanner-Service für Autohäuser; Schwerpunkt Versicherer und Autohäuser.
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TÜV Rheinland Adomea – Deutschland; mobiler Durchfahrtscanner, vor allem für Hagelschäden; nicht mehr am Markt.
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TÜV SÜD Digital Vehicle Scan – Deutschland; Durchfahrtscanner inkl. Unterboden für Pkw bis Lkw und Busse; nicht mehr am Markt.
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Twinner – Deutschland; Großscanner für Händler und Hersteller; nach Insolvenz seit 2024 nicht mehr am Markt.
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TwoTronic – Deutschland; Durchfahrtscanner, Reifen und Glasschäden; KI unbekannt; Schwerpunkt Hersteller und Werkstätten.
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UVeye – Israel; Unterbodenscanner; Schwerpunkt Hersteller, Händler, Vermietung und Lieferflotten; laut Anbieter über 3 Mio. gescannte Fahrzeuge pro Monat (2026).
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Verisk IVI – USA; Bilderkennung zur Einteilung in Reparatur oder Totalschaden; Schwerpunkt europäische Kfz-Versicherer.
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Wenn / CarEye – Norwegen; Scan-Tunnel; Schwerpunkt Autovermietung an Flughäfen; laut Anbieter über 300.000 Scans pro Monat.
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WeProov – Frankreich; App; Schwerpunkt Vermietung und Versicherungsschäden; laut Anbieter über 10 Mio. Fahrzeugchecks insgesamt (2025).
What should you look for when choosing a system?
Detection quality: Quality varies considerably in some cases; some systems still rely on assessors who review images remotely. Another important question: who checks a finding before a driver or customer is held responsible? Otherwise, wrongly detected old damage causes trouble.
Limits with small damages: Practically every system detects larger damages. With small damage such as stone chips, most systems reach their limits or need images taken from very close up. As a rule of thumb: what the human eye cannot see, the AI cannot detect either. For lease returns, where every small damage counts, the technology therefore reaches its limits sooner than in commercial vehicle fleets, where the main focus is on new damage and who caused it.
Provider experience: Many providers have so far mainly carried out pilot projects. Only a few already inspect millions of vehicles – and therefore have a correspondingly large data basis for their AI.
Ease of use for drivers: With apps, ease of use determines success in day-to-day operations. Good solutions help the user position the camera and automatically check image quality while the photo is being taken.
Processing time: Depending on the system, detection takes between about one minute and 15 minutes, depending on the performance of the AI and the internet connection. How important this is depends on how quickly the results are needed – for example during the vehicle handover or only later for billing.
Integration: Some providers only supply their own app or web interface, others can be connected via an interface (API) to fleet management software, telematics or claims management. Ideally, damage detection is integrated directly into the app that drivers already use – for example the fleet management software app.
Data protection and works council: Where are the images stored and processed, and are drivers or number plates recognisable? If the system assigns damage to individual drivers, the works council usually has to be involved in Germany – this should be planned early in the project.
Conclusion: There is no single right technology – which solution fits depends on the use case: How many vehicles need to be inspected, where are they handed over and who takes the pictures?
What should you look for when choosing a system?
Detection quality: Quality varies considerably in some cases; some systems still rely on assessors who review images remotely. Another important question: who checks a finding before a driver or customer is held responsible? Otherwise, wrongly detected old damage causes trouble.
Limits with small damages: Practically every system detects larger damages. With small damage such as stone chips, most systems reach their limits or need images taken from very close up. As a rule of thumb: what the human eye cannot see, the AI cannot detect either. For lease returns, where every small damage counts, the technology therefore reaches its limits sooner than in commercial vehicle fleets, where the main focus is on new damage and who caused it.
Provider experience: Many providers have so far mainly carried out pilot projects. Only a few already inspect millions of vehicles – and therefore have a correspondingly large data basis for their AI.
Ease of use for drivers: With apps, ease of use determines success in day-to-day operations. Good solutions help the user position the camera and automatically check image quality while the photo is being taken.
Processing time: Depending on the system, detection takes between about one minute and 15 minutes, depending on the performance of the AI and the internet connection. How important this is depends on how quickly the results are needed – for example during the vehicle handover or only later for billing.
Integration: Some providers only supply their own app or web interface, others can be connected via an interface (API) to fleet management software, telematics or claims management. Ideally, damage detection is integrated directly into the app that drivers already use – for example the fleet management software app.
Data protection and works council: Where are the images stored and processed, and are drivers or number plates recognisable? If the system assigns damage to individual drivers, the works council usually has to be involved in Germany – this should be planned early in the project.
Conclusion: There is no single right technology – which solution fits depends on the use case: How many vehicles need to be inspected, where are they handed over and who takes the pictures?
Our services: Consulting regarding AI damage detection
We help you to select the best supplier for AI based automatic vehicle inspection and damage detection. Our consulting services comprise:
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Analysis of your company specific goals, processes and existing other technologies used
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Market overview: Overview over systems for AI automatic vehicle inspections / vehicle scanners
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Selection: Identification of suitable suppliers, tendering, negotiation, cost planning, pilot-phase.
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Implementation of new AI system
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Supplier management: Definition of SLA/KPI and continuous quality control.
CONTACT US directly so we can define how to help you.
ClearQuote
Based on our experience in the remarketing, vehicle inspection and fleet management industry we recommend ClearQuote AI based automatic vehicle inspections.
We see ClearQuote as a market leading solution that fits the use cases of many companies of various industries.
We support ClearQuote in their market activities in Europe.
ClearQuote Features:
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AI based vehicle inspection/ damage detection
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Passenger cars, SUV, pickups, transporters, box-vans, bicycles
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Works with simple smartphones and fixed vehicle scanners
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Realtime quality check while taking the pictures
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Detects damages: dents, scratches, wheel/ alloy damages, broken parts, broken screens
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Identifies new damages by comparing pictures now vs. previous time (check-in/check-out)
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Calculates repair costs, based on internal data or via integration to 3rd party database
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With own IOS/Android-App, or integrated into your systems via API
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Additionally reads out VIN, numberplate and mileage
Customers
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Real paying customers: Over 500.000 inpections per month!
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References: OEM vehicle manufacturer, insurance, leasing & fleet management, claims handling, vehicle inspection, tranporter fleets, car rental
Awards
In November 2022 ClearQuote won the PIP Startup Innovation Award of the Postal Innovation Platform (PIP), sponsored by Swiss Post, Austrian Post and the Parcel+Post Expo. ClearQuote also won another aard in the category of "Processes, Digital & Data"
Postal Innovation summarizes: "ClearQuote's solution is ... smart, facilitates the work and processes of postal and logistics providers considerably, and also shows a sound and proven concept". See more info in this video.
In February 2022 ClearQuote was announced the winner of the DHL Middle East Fast Forward Challenge.
DHL states: "ClearQuote is a mobile application utilising cutting edge technologies to conduct fast, reliable and transparent vehicle damage assessments and maintenance valuing, using smartphone images and computer vision."
CONTACT US directly in order to get a free online demo of the ClearQuote system!