From “I’m looking for” to confident purchase.
Conversational AI that knows your catalog, speaks your brand and guides the decision — for humans and AI agents alike. Grounded in your catalog, your brand voice and live signals like inventory and pricing.
The shift
Product discovery is broken, and shoppers are leaving because of it.
- 01
Search that doesn't understand intent.
A shopper types “warm living room light” and gets a list of SKUs sorted by relevance score. No context, no questions, no trade-offs explained. They scroll, skim and leave.
- 02
Filter walls that paralyze.
Dozens of facets, hundreds of checkboxes and zero guidance on which ones matter. The shopper who doesn't already know what they need is the one most likely to abandon.
- 03
No one to explain the trade-offs.
Two products, different specs, similar price — and nothing on the page explains which one is right. In a store, someone would answer that. Online, the shopper figures it out alone or doesn't.
- 04
Built for humans only.
AI agents query catalogs and evaluate products on behalf of the people they serve. A storefront with no structured, queryable interface is invisible to that traffic.
Live demo
A designer's sidekick that knows your catalog.
Shoppers describe what they are after in plain English. The assistant queries your live catalog, surfaces the best fits and adds the picks to their project.
Active project
Loft Reading Nook
Assistant · live tools
user
Designing a reading nook in my loft — walnut tones, warm and cozy.
Active project
Loft Reading Nook
Assistant · live tools
user
Designing a reading nook in my loft — walnut tones, warm and cozy.
assistant
Got it. Pulling pieces from your partners that match your saved style.
- query_inventory
- get_pricing
- style_match
- your_partners
Active project
Loft Reading Nook
Boucle Swivel
Lounge · oat
$1,42096% match
Walnut Drum
Pendant · 18"
$68092% match
Field Side Table
Walnut · round
$54089% match
Reverie Runner
Rug · 3×8
$39086% match
Assistant · live tools
user
Designing a reading nook in my loft — walnut tones, warm and cozy.
assistant
Got it. Pulling pieces from your partners that match your saved style.
- query_inventory
- get_pricing
- style_match
- your_partners
assistant
4 matches found — best fit first, all in stock.
What's built in
An assistant for shoppers — and the agents shopping for them.
Intent-first discovery
Starts with the shopper's goal, not a keyword. Asks the right clarifying questions and narrows by what actually matters — room size, use case, compatibility.
Catalog-grounded answers
Every response pulls from your enriched product catalog — your products, your specs, your inventory, your pricing. The assistant doesn't recommend products you don't carry.
Honest comparisons & trade-offs
When a shopper is deciding between two products, the assistant explains where each one wins and where it falls short for their situation. Confidence, not pressure.
Your voice, your policies
Configured to speak in your tone — your terminology, your way of handling objections, your category vocabulary. It represents your brand, not a generic chatbot.
Live inventory & pricing signals
Inventory, pricing and lead times in real time, so recommendations stay accurate at the moment they are made.
Smart support deflection
Order status, spec lookups, compatibility checks, return policies — answered from your data. Human attention is reserved for the conversations that need it.
Clean human handoff
When a question needs a person, the assistant transfers with full context attached. You define the escalation rules; it follows them.
Multi-surface deployment
The same assistant across your website, internal tools and channel-specific surfaces. One configuration, consistent answers.
Agent-ready
The same conversational layer that serves humans responds to structured queries from AI shopping agents. No separate integration, no second build.
Governed and auditable
Every response logged, every escalation tracked, every data source cited. You always know what the assistant said, when, and where the answer came from.
Questions
Asked before you ask.
What does the assistant actually know about our catalog?
Everything you give it access to — products, specifications, pricing, availability, brand guidelines and any context your team has built into the system. It answers from your catalog, not the open web. If a product isn't in your data, the assistant says so rather than guessing.
How is this different from a search box or filter panel?
A search box returns results for whatever words the shopper typed. This assistant asks clarifying questions, understands intent, compares trade-offs honestly and explains why a product is or isn't a good fit. It guides — it doesn't just retrieve.
Can it handle complex or high-consideration purchases?
Yes — that's where it adds the most value. For products where compatibility, specifications and trade-offs matter, the assistant can walk through the decision step by step.
Does it work for AI agents, not just human shoppers?
Yes. The same assistant logic that guides a human through discovery also handles structured queries from AI agents shopping on behalf of a customer.
Where does the assistant hand off to checkout?
The assistant brings the shopper to a confident decision, then surfaces a clear path to purchase — cart, product page, or a direct hand-off to your existing checkout flow. It doesn't own checkout; it removes the friction before it.
How is pricing structured?
Based on catalog size, traffic volume and integration complexity. We scope it after understanding your stack — you'll have real numbers before committing to anything.
Keep exploring
More in Technology.
- Marketing InfrastructureFragmented catalogs and siloed systems become structured, agent-accessible architecture — the data layer that decides whether agents can find you.
- Semantic SearchVector-native semantic search that understands intent, context and natural language — typo-tolerant, behavior-trained, queryable by humans and AI agents alike.
- PricingOne plan launches your storefront, adds your products and services, imports your customers and gets you paid — plus capacity and Neural Labs services when you want them.