Private alpha for professional damage intake
AI-assisted vehicle damage intake for expert review teams
Autolense helps claims and assessment teams collect complete photo evidence, validate capture quality, extract vehicle data, and prepare structured damage reviews without replacing the professional decision maker.
Reviewer queue
Case AL-2481
Front
Driver rear
Damage
VIN
Odometer
Registration
Assessment
Front bumper and left fender damage detected. Human review recommended before final estimate.
Built for
Teams that need reliable first intake, not another generic chatbot
Insurance carriers
Collect consistent photo evidence and structured claim data before a reviewer opens the case.
Independent vehicle assessors
Guide customers through the first intake and keep the final assessment under professional review.
Repair and fleet teams
Standardize incoming damage documentation across vehicles, locations, and external drivers.
Current capabilities
Focused on capture quality, structured data, and reviewability
The product is in private alpha. The goal is to reduce incomplete submissions and make the first review faster, while keeping final judgment with trained teams.
Browser-first mobile capture through private submission links
Guided document, overview, and damaged-part photo flows
Image metadata extraction, preprocessing, thumbnails, and quality checks
Pose and subject validation for documents, vehicle overviews, and damaged areas
Vehicle field extraction from registration, VIN, and odometer photos
Submission-level damage assessment with evidence photos and human review
Workflow
From private link to reviewer-ready case
01
Create a case
A team member creates a submission in the dashboard and sends an expiring mobile link by SMS, email, or copy-paste.
02
Capture evidence
The customer opens the link in a mobile browser and captures required documents, vehicle overviews, selected damaged parts, and questionnaire answers.
03
Process the images
The pipeline stores originals, extracts metadata, creates processed artifacts, checks quality and perspective, and asks for retakes when needed.
04
Review the result
AI-assisted extraction and damage assessment are shown in the dashboard with job status, evidence photos, model telemetry, and reviewer controls.
Private alpha
Request access for your assessment workflow
Join the waitlist to discuss fit, test the browser capture flow, and evaluate the AI-assisted review pipeline with a small set of private cases.