Collect
Bring photos, video, documents, sensor readings and transaction records into one case.
Platform overview
Cross-check photos, video, paperwork and system records against each other and your rules. Surface inconsistencies, identify what’s missing, and move each case to the right next step.
Lending · Insurance · Logistics · Property · Construction · Evidence integrity
From evidence to action
Collecting a file is only the beginning. VerifyAI connects what it shows, what other records say, and what your business needs to do next.
Bring photos, video, documents, sensor readings and transaction records into one case.
Extract the details that matter: identities, conditions, amounts, locations and events.
Compare sources, find contradictions and separate missing evidence from a failed check.
Apply your rules. Approve routine cases, request more evidence or route exceptions to a person.
Keep the evidence, findings and decision together. Send the result into your workflow.
See how it connects
Follow the evidence through a case. See why a check passed, where records disagree, and what the workflow requests next.
Example workflow / Application L-2048
Select a source to trace its findings.
What agrees, what conflicts, what is missing.
The visible VIN matches the application and title.
The odometer reads 64,210 miles; the application declares 42,000. Review the discrepancy before relying on the valuation reference.
Request an interior view before completing the condition review.
If a required view is missing or mileage conflicts, request evidence and route to review.
Illustrative records and outcomes. Your evidence requirements, decision rules and review thresholds define the workflow.
Control, built into the workflow
Give your team a reviewable trail from submission to action, including the evidence, checks, exceptions and final decision.
Connect conclusions to the image, document or event that supports them. Keep contradictory evidence visible.
Separate an incomplete record from a failed check. Ask for the specific evidence needed to move forward.
Set required evidence, thresholds and exceptions. Keep human review where judgment matters and automate routine routing.
Built around your decision
Start with the question your team needs to answer. Connect the evidence and rules around it.
Connect collateral photos, application details, ownership documents and valuation references before making a lending decision.
Explore lending 02 / InsuranceCross-check damage evidence, policy details, estimates and prior records so reviewers can focus on what needs a closer look.
Explore insurance 03 / LogisticsConnect delivery photos, shipment records, scans and location events into a clear account of each shipment.
Explore logistics 04 / PropertyCompare property condition, work orders, before-and-after evidence and invoices in one review workflow.
Explore property 05 / ConstructionBring site photos, inspection records, delivery documents and contractor updates together before approving the next step.
Explore construction 06 / Evidence integrityCross-check identities, dates, locations and records across submissions to surface suspicious patterns and conflicting evidence.
Explore evidence integrityFit verification into your product
Capture through your application or a guided link. Connect verification results to your systems through APIs and webhooks. Start with a defined check, then expand around the decisions that matter.
From capture and individual checks to reports, integrations and operational workflows.
Server-managed analysis with mobile-friendly UX.
VerifyAI pairs mobile capture SDKs with a hosted verification API so policies, prompts, and model behavior can evolve server-side without forcing app releases. The result is a fast user flow with centralized control over verification logic.
Fast Hosted Verification
Understands context, not just pixels.
Unlike simple image classification, VerifyAI understands the full scene context. It identifies sidewalks, bike racks, doorways, parking zones, vehicles, packages, and obstacles. This semantic understanding enables accurate verification even in complex real-world environments.
Semantic Scene Understanding
Keep moving through poor connectivity.
Supported SDK flows can queue transient failures locally and replay them when connectivity returns. That keeps field operations moving in poor-connectivity environments without pretending every capture path is fully offline.
Offline Retry Workflows
Control what you send and how long it lives.
Images are transmitted only when needed for verification, over encrypted channels, with configurable retention and regional storage options. Customers stay in control of submitted metadata, retention policy, and downstream access.
Privacy-First Architecture
Turn any rule into an AI model.
Translate complex verification requirements into executable policies. Define what constitutes compliant parking, acceptable delivery placement, or passing damage inspectionâthen deploy instantly. Update policies server-side without app updates.
Policy-as-Code
Insights, not just data.
Track compliance rates, violation hotspots, fleet health, and operational trends in real time. The VerifyAI dashboard provides actionable insights that help you optimize operations, reduce costs, and improve compliance.
Real-Time Analytics
Models improve automatically.
VerifyAI models are continuously retrained on new data to improve accuracy over time. Monthly model updates are pushed automaticallyâno manual intervention or additional cost. Your verification accuracy improves every month.
Continuous Learning
Built for regulated industries.
Runs on infrastructure from providers with SOC 2 Type II reports (Vercel, Supabase, Google Cloud), with built-in fraud prevention that detects duplicate photos, AI-generated images, and metadata tampering. Role-based access control, full audit logs, and SSO integration for enterprise compliance requirements.
Enterprise Security
Per-panel damage with severity, industry-standard codes, repair-cost dollars, and pickup-vs-return delta. Built for insurance, leasing, rental, and finished-vehicle logistics.
Per-panel damage findings with type (dent, scratch, crack, paint chip, missing, misalignment, rust) and severity (none, light, medium, severe). Opt-in per policy via damageMode â existing parking and POD policies are unaffected.
Damage findings transform automatically into industry-standard grading frameworks. AIAG codes for North American finished-vehicle logistics, K1âK5 for European leasing. Pure server-side transform, no extra API calls.
Turn damage findings into dollar repair estimates via Mitchell Cloud Estimating API. Aggressive server-side caching, fail-soft if Mitchell times out. GT Motive (EU) on roadmap.
Pair a check-out verification with a check-in verification and the engine surfaces only new damage attributable to the rental. IoU>0.3 matching with panel-not-visible exclusion to suppress false positives from differing angles.
Capture inspections from end users without forcing an app install. Branded artifacts your customers actually sign and store.
Send a renter, claimant, or driver a single signed URL. They open it in mobile Safari or Chrome, are walked through each required shot, and sign on completion â no app install. Token-authenticated, HMAC-signed, DB-hashed for revocation.
Branded PDFs with annotated damage overlays, vehicle block (VIN / plate / timestamp), and signature panel. Cached to private Supabase storage; signed URL on demand. Renders the damage section automatically when damageMode is on.
Read VIN and plate from a single photo. ISO-3779 checksum validation, then NHTSA vPIC decode to make / model / year / trim â cached indefinitely. Privacy guardrail: we never look up plates against owner databases.
What enterprise procurement asks for: site-scoped access, exception triage, append-only audit log, claims-platform integrations, and BI export.
Scope verifications to specific sites (yards, dealer lots, depots). Org owners and admins see everything; site managers and viewers only see their assigned sites. Site resolution from metadata.site_external_id or X-Verify-Site-Id.
Low-confidence and non-compliant verifications open an exception automatically. Assign to a teammate, add notes, mark resolved or dismissed. Every state transition is audit-logged.
Append-only log of every state-mutating action across the dashboard and API: API key rotations, member changes, policy edits, integration deliveries, exception transitions. Kept as compliance evidence for enterprise security reviews.
Push verification events into claims platforms. Adapter registry pattern with retry queue (1m / 5m / 30m / terminal). Guidewire ClaimCenter adapter stub shipped; Duck Creek and Mitchell on roadmap.
Signed-URL CSV or JSON exports of verifications, exceptions, or audit log for downstream BI. 50,000-row cap per request; respects site-scoping. v2: direct connectors via Fivetran / Stitch.
Channels and adapters built for specific verticals: WhatsApp for EMEA/LATAM insurance, BOL OCR for freight, chargeback defense for retail suppliers, TMS adapters for trucking.
Conversational photo capture over Twilio WhatsApp Business API. State-machine guides the user through each shot (greeting â consent â instructions â captures â review â submitted). Critical for markets where WhatsApp is the default channel.
Extract bill-of-lading fields from a photo: BOL number, PRO, weight, freight class, addresses, pieces. Powers chargeback-defense automation. Structured-output extraction with a Zod-validated response.
Auto-draft dispute letters for Walmart OTIF, Amazon Vendor, Target, Kroger deductions. 10 prebuilt templates seeded; customer-specific templates take precedence. Dispute drafter joins verification â shipment â template.
Adapter stubs ship with the documented config shape for McLeod LoadMaster (REST/IFS) and SupplyPike (Bearer + HMAC inbound webhook). Wire them to your tenant credentials when ready. Cargowise + MyEZclaim on roadmap.
Production-grade ML platform: targeted model dispatch, canary rollouts, drift detection, and drive-through camera streams. Built so the team can ship models with confidence.
Ship different models per asset type, region, customer, or app version. Production / canary / shadow tiers with sticky bucketing via SHA-256 hash of customer_id + device_id. Roll out canaries to 10% of traffic, monitor, promote.
Population Stability Index over feature + result distributions, computed hourly against a reference snapshot taken at promotion. Sentry alert on PSI > 0.25. Cleanup of recent_inferences runs in the same cron tick.
Per-frame verification endpoint for fixed drive-through cameras. QR-pair flow mints a long-lived stream_token (bcrypt-hashed in DB) from a short-lived one-time code. Sync verification result returned in <800ms.
Train your own RT-DETRv2-derived detector on a custom policy. Datasets in verify_ai_ml_samples (COCO JSONB), training via the ml/ Python pipeline, bundle registration via register_bundle.py. Lineage tracked at the bundle level (git_sha, training_dataset_id, gold_eval_results).
Start with a free sandbox account. Test every feature with no credit card required.
Tell us about the evidence, the decision and the workflow around it.