Scale AI and Appen dominate commodity annotation — bounding boxes, transcripts, basic tags, priced by the millions. We do the opposite: small, high-judgment datasets where the label itself requires fashion sense, retail strategy, media literacy, or advertising instinct. Work a general crowd can't reliably do.
Bespoke, context-rich annotation for AI teams building shopping assistants, retail analytics, and synthetic media models — sold as a strategic retainer, not a per-label rate.
Foundation models handle the easy labels now. What's left is the hard part.
AI models can now pre-label a routine bounding box or a basic sentiment tag almost as well as a human. That's collapsed the price of commodity annotation and pushed the entire industry's demand toward the edge cases: the labels that require actual expertise to get right — merchandising sense, retail strategy, media literacy, brand judgment.
That's exactly the kind of judgment a marketing agency already has. We're not trying to out-scale Scale AI. We're building narrow, expert annotation programs in categories where "does this look right to a human who knows the category" is the entire task.
We don't compete with Scale AI or Appen on price-per-label — that's a race to the bottom against firms built for commodity volume. Instead we package this as a strategic engagement: an audit and pipeline design, followed by an ongoing managed retainer, the same way we sell every other service.
We'll scope a pilot batch — typically returned within a week — so you can see the quality before committing to a program.
Scope a Pilot Batch →