About ImageHub

We started as a small engineering team facing a familiar problem: ecommerce imagery is messy, lacking metadata, inconsistently encoded, and often stored in ad-hoc folders that make automation impossible. Over the last few years we've built a pragmatic, metadata-first toolkit that turns these messy inputs into structured, audit-ready datasets.

Our philosophy is simple: preserve fidelity, make metadata primary, and keep an auditable trail. When we process images we record every transformation, preserve original bytes whenever possible, and export a single canonical metadata file per folder so your systems can rely on a stable contract.

Mission and approach

Our mission is to reduce friction for merchants and data teams. Instead of building one-off scripts that fail at scale, we provide robust, documented tooling and workflows that are predictable and auditable. We believe in small contracts: a defined metadata schema, append-only mapping logs, and reproducible exports.

What we build

We build a pipeline that addresses the full lifecycle of ecommerce images:

• Discovery and conversion: Detect extensionless files, copy or re-encode based on policy, and maintain mapping records.
• Metadata enrichment: Extract EXIF, compute dimensions, tokenize paths into categories, and optionally run OCR or CV labelers.
• Exports: Produce per-folder metadata JSON and CSV for Rails imports or ML pipelines.
• Delivery: Publish to S3-compatible storage or provide time-limited ZIP downloads with audit logs.

Why our approach helps startups

Startups and small teams benefit from predictable, repeatable data processes. By standardizing images and shipping metadata-first exports, product and engineering teams can:

• Reduce manual mapping work during imports
• Lower labeling costs by providing pre-filtered candidate sets
• Accelerate model iteration with consistent training inputs
• Improve catalog conversion by surfacing canonical primary images and clean tags