AI agents for your
ecommerce team.
Improve search, ranking, and product content.
Give shoppers more to find. And your team less to do.
Illustrative agent workspace. Sample catalog.
Meet the agents behind better product discovery.
Recover missed searches.
Help recurring failed searches connect with products you already carry. Recovery finds missed matches and prepares supported search improvements for your review.
Get startedSearch recovery
Shopper search
black flare yoga pants
Form Flare Pant
Black · High rise · Flared
Catalog matchScale product discovery
with an AI team you control.
We handle setup. You stay in control.
We connect Regor to your storefront and catalog, configure the agents for your environment, and help you choose which supported changes to review or automate.
Meet your AI team- Compatible with your existing stack
- Improves search relevance, product ranking, and catalog quality
- Review changes or automate eligible actions
- Every supported change is verified and reversible
The product discovery stack
One team.
No disconnected decisions.
Your agents share the same shopper signals, product knowledge, and rules. Search, ranking, and product content work together, with your team in control.
From spotting the problem to making a supported change and measuring what happened, every step stays connected.
Regor brings shopper behavior and product facts together to find recurring searches, products, and discovery journeys that need attention.
The agents compare supported changes across search, ranking, and product content. Sometimes the right decision is to leave things as they are.
You choose where Regor observes, asks for approval, or makes eligible changes automatically. Your rules are checked again before anything runs.
Regor applies the supported improvement through the connected system, then checks that the resulting state matches the intended change.
Follow what happened after the change. Regor keeps the results and the strength of the evidence visible, so you can see what is known and what is still uncertain.
Your team sets the boundaries.
One connected workflow
- Evidence
Understand what shoppers are missing
Shopper signals + product facts - Decisioning
Compare the available improvements
Search, ranking, content, or no change - Control
Check your rules and approvals
Your policies, checked before execution - Execution
Apply the improvement and verify it
Supported action + result verification - Measurement
Bring the results back to your team
Measured outcomes + evidence strength
Why search matters
Search is where shopper intent becomes measurable.
Search shows what shoppers are actively trying to find, where relevant products are being missed, and where better discovery decisions can be connected to downstream behavior.
10,773,986
shopper behavior signals analyzed
Search, product-view, and purchase activity across an anonymized ecommerce dataset.
73.5%
of purchasers searched before buying
Search appeared in nearly three out of four converting journeys in the analyzed sample.
High-intent signal
Search captures what shoppers are actively trying to find, not just what pages they happened to visit.
Measurable failure
Weak results, failed queries, and missed product matches reveal where existing demand is being lost.
Close to revenue
Search behavior can be connected to product engagement and resulting orders when the evidence supports attribution.
Based on an anonymized enterprise ecommerce behavioral sample. Directional evidence, not a category-wide benchmark.
Full security and governance detail lives in the Trust Center.
FAQ
Common questions
Does Regor make changes automatically?
Yes, when you enable it. You set how far it goes, from watch-only, to approving each change, to permitting eligible low-risk actions to run on their own. Policy, tenant state and activation are checked again at execution, so an action that is no longer eligible does not run. High-impact changes can always wait for your review, and every action is recorded before it executes, so autonomy never means losing the audit trail.
Can Regor work with my existing search provider?
Regor is designed to work alongside your provider, not replace it. It finds where shoppers fail to reach products you already carry, then turns each finding into a proposed change. With Algolia, Regor can write approved changes through a Regor-managed namespace and defers to rules your team already manages. Regor does not currently write to Searchspring. There it identifies the gaps and presents proposed remediation for your team to apply.
How does Regor measure impact?
Regor records an action before it executes, then links directly attributed order events back to that action. Separately, eligible query and product actions are evaluated against matched controls where enough controls exist. Results that qualify receive a causal estimate with a 95% confidence band. Results that do not are labeled underpowered, contaminated, or pre and post, rather than presented as proven lift.
Can Regor improve my products’ visibility in AI search?
No platform can guarantee placement inside a third-party assistant, and we will not claim otherwise. What Regor does is add grounded tags and product descriptions built from verified catalog facts, so search systems and AI shopping assistants have cleaner, more complete product information to interpret. The claim is better machine readability, not guaranteed visibility.
Which ecommerce platforms does Regor support?
Headless and custom API stacks, BigCommerce, Adobe Commerce and Magento, and WooCommerce, alongside Algolia, Searchspring and Typesense. Write-back depends on provider capability and account configuration: Algolia supports it today, while Searchspring is audit and observe only. No replatforming is required.