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Image classification

Classify Any Image, In-Browser.

This is a general-purpose vision classifier, not a diagnostic model — we're showing the mechanics of an in-browser imaging pipeline (upload → preprocess → inference → ranked output), the same shape as the modality-specific models we build for imaging engagements.

Model ViT Base (patch16-224)
Run time ~90 MB first run only
Input Image
The image that will be classified
Sample Image
Top Predictions Confidence

Classify the image above, or choose one of your own, to see the model's five most likely labels out of the 1,000 everyday categories it was trained on. The model downloads once (~90 MB) and then runs entirely in your browser — the image never leaves your machine.

Case Studies

See how organizations are leveraging our AI solutions to scale.

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Automating Invoice Processing for Pacific Financial

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99.1% Extraction Precision Read Case Study
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AI-Powered Resume Screening at TalentForge

TalentForge integrated neural search embeddings to screen millions of developer candidate portfolios accurately.

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Vervelo is a digital-health software partner blending deep clinical insight with world-class engineering to build tailored, secure, interoperable healthcare platforms.

Benefits of custom software solutions
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What services does Vervelo offer?

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Do you provide custom CRM solutions?

Yes, we design and develop fully custom CRM solutions tailored to your workflows.

Can these AI solutions run on our own infrastructure?

Yes. Every solution on this page is built to run inside your environment — on your machines, with your data staying where it is.

How long does a typical engagement take?

Most pilots go live in four to six weeks, with production rollout following once the results are validated against your data.

Do you fine-tune models on our data?

We do, where it earns its keep. Many of these solutions start from open models and are tuned against your domain data.

How do we get started?

Send us a note through the form above and we will set up a working session with the engineers who would build it.

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