VerifyAI vs Captur.ai

Captur uses a committed pricing model with annual platform fees. Their Pro plan starts at $40,000/year in platform fees plus $0.02 per event, with a $5,000/month minimum. The Enterprise plan jumps to $120,000/year plus $0.009 per event with a $12,500/month minimum. Getting started requires a sales conversation and enterprise contract.

VerifyAI charges a flat $0.008 per verification with no platform fees, no monthly minimums, and no annual commitment. Volume pricing drops to $0.005 at 100K/month and $0.003 at 1M+/month. You can sign up and start integrating immediately.

For an operator processing 200,000 verifications per month, VerifyAI costs roughly $1,000/month. Captur's Pro plan would cost approximately $8,333/month ($5K minimum + overage), plus the $40K/year platform fee amortized monthly. That's over 80% savings with VerifyAI.

Both platforms use on-device edge processing, meaning AI inference runs locally on the user's phone rather than in the cloud. This enables sub-second verification times and offline capability.

Captur reports 1.5 billion on-device inferences over a 6-month period across 3,000+ device types, with models under 10MB. They use TensorFlow Extended with knowledge distillation to compress models for mobile. They report 80%+ mis-parking reduction and 96% POD compliance in case studies, though they do not publish raw accuracy metrics.

VerifyAI achieves 99.2% accuracy across parking verification, damage detection, and proof of delivery. Model retraining is included on all plans and custom model training is available for Growth and Enterprise customers.

Captur's SDK supports iOS, Android, React Native, and Flutter. Integration is described as taking one sprint (roughly 2 weeks), with some customer case studies reporting 4 weeks from start to production. SDK documentation is hosted on a gated readme.io portal, and their API docs use Stoplight.

VerifyAI's SDK is designed for 3-line initialization with drop-in components for iOS, Android, React Native, and Flutter. Most teams are live within a day. Full documentation and sample apps are publicly available without requiring a sales conversation.

The key difference is access: VerifyAI is self-service from signup to production, while Captur requires going through a sales and onboarding process before you can start integrating.

Both platforms cover the core micromobility and logistics verification use cases: parking compliance, proof of delivery, and damage detection. Both include automatic face and PII blurring for GDPR compliance, and fraud prevention features including duplicate photo detection and AI-generated content filtering.

VerifyAI covers parking verification, damage detection, and proof of delivery with an emphasis on fleet inspection workflows. Captur extends into ecommerce/resale photo authentication. Both platforms support customizable compliance rules and configurable policies.

For the core micromobility, delivery, and fleet use cases, both platforms are fully feature-comparable. Captur's ecommerce/resale niche is a separate vertical that most micromobility operators don't need.

Captur was founded in 2020, has raised approximately $4.3M, and employs around 33 people. They are deployed in 50+ countries with published case studies from Veo, GoBolt, Dott, Forest, Buzzbike, and Zapp. They entered the U.S. market in October 2024 through a partnership with Veo across 50+ cities.

VerifyAI is newer to market with a focus on transparent pricing, developer-first integration, and cost efficiency. While Captur has more published deployment history, VerifyAI's architecture and feature set are comparable.

If vendor maturity and reference customers are your top priority, Captur has the edge. If cost, speed to integrate, and contract flexibility matter more, VerifyAI is the stronger choice.