Customers search with a photo,
not a guess at the right keyword
A customer who sees a product they like somewhere else rarely knows the right keywords to find something similar in your catalogue, and text search cannot help with a request that starts as a photo. We build a visual search agent that indexes your catalogue by appearance and lets customers search with a photo, returning ranked matches instead of a dead-end keyword search.
The process today
A customer sees a product they want somewhere, in a photo a friend sent, on social media, in a store they walked past, and tries to find something similar in your catalogue using a text search box that needs the right keywords to work. Most of the time they do not have those keywords, they have a picture in their head and a photo on their phone, and text search simply cannot bridge that gap, so the customer either gives up or scrolls through categories hoping to spot it.
The second cost is the SEO and keyword gap for products that are hard to describe precisely, a specific pattern, a particular silhouette, a color that does not map cleanly to a standard name, where even a motivated customer struggles to type the right search term.
The third is the lost signal: every one of these failed text searches is a real demand the catalogue had an answer for, but the search experience could not connect the two, and that gap rarely gets measured because there is no easy way to see what a customer was trying to find with an image.
None of this shows up as one dramatic failure. It shows up as a steady drag: visual search for catalogues work that should take minutes stretching into a backlog item, a quality bar that holds on a quiet week and slips on a busy one, and a team that knows the fix is mechanical but never has a free afternoon to build it themselves.
What the agent does
The agent builds a visual index of your catalogue from existing product photos, encoding what each product looks like rather than only its text description, and exposes a photo upload option on your storefront or app search. When a customer uploads a photo, it matches against the index and returns ranked results by visual similarity, with a confidence score so results stay honest about how close a match actually is.
As new SKUs are added through your normal product feed, the index updates automatically, so visual search stays current without a manual re-index step every time the catalogue changes. Where no strong visual match exists, the experience falls back to text search rather than showing a confident-looking but wrong result.
Typical integrations: your product feed or PIM as the source of truth for the catalogue, and your storefront or app’s search interface for where the photo upload option appears.
What stays with humans
Deciding how prominently to surface visual search in the shopping experience, and interpreting what the search analytics reveal about unmet demand, are calls your merchandising team makes. The agent returns ranked matches by appearance; it does not decide pricing, placement or which gaps in the catalogue are worth filling based on what customers are searching for.
Guards
Similarity thresholds start conservative, so a weak match falls back to text search rather than being shown as a confident result, and are tuned against your actual catalogue before launch rather than a generic benchmark. Search analytics are logged in aggregate, so your team can see demand patterns without the pipeline needing to retain customer-uploaded photos longer than the search itself requires.
Before it runs unattended, we run a side-by-side dry run against a sample of your own visual search for catalogues material so your team can see exactly what it would have done. Every build ships with a short written runbook so your team can pause it, adjust a threshold, or roll it back without waiting on us, and the running-cost estimate below is a starting budget you set, with an alert built in before it is crossed.
Price and timeline
| Option | Price | What it covers | Timeline |
|---|---|---|---|
| Single automation | from $1200 | Visual index built from your existing catalogue photos | 8 to 15 days |
| Department package | from $2,500 | visual search, product descriptions and catalogue photo quality across your ecommerce team | 2 to 4 weeks |
Running cost is usually $10 to $80 a month in model usage depending on volume, with a budget cap set before launch.
Related
Pair this with product tagging for real estate listings if your catalogue spans listings rather than SKUs, and with product photo quality check to keep the indexed photos themselves consistent. For the product data side of search relevance, see product descriptions at scale. The full package breakdown is on the AI agents service page and the e-commerce service page; for a real build of a catalogue-heavy storefront, see the Thailand D2C store rebuild case study and the Telegram marketplace engine case study.
Ready to let customers search with a photo instead of a guess? Get in touch and we will test it against a sample of your catalogue in the first call.
Tired of doing this by hand? We can take the whole routine off your team, not just this step: Routine takeover, from $400 →
FAQ
How much does visual search cost?
from $1,200 to index your catalogue and integrate photo search into your storefront, live in 8 to 15 days depending on catalogue size.
Does this replace our existing text search?
No, it adds photo search alongside it, with a fallback to text search when no strong visual match exists, so neither customers nor your SEO lose anything that already works.
How does it stay accurate as we add new products?
The catalogue index updates automatically as new SKUs are added through your normal product feed, without a manual re-index step each time.
What can customers search with besides their own photos?
A photo taken on their phone, a screenshot from social media, or an image from another site all work the same way; the agent matches by visual similarity, not by where the image came from.
Does it work well on a catalogue with similar-looking products?
Accuracy depends on how visually distinct your SKUs are from each other; we tune the matching and ranking on your actual catalogue before launch rather than shipping a generic default.