AI systems for modern commerce

Models and infrastructure for understanding customers, products, behavior, and business state in real time.

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Powering commerce experiences at scale

KICKS CREW
Mejuri
Shutterstock
SwimOutlet
MUJI
RC Willey
Dooney & Bourke
Kogan

What teams run on Celeris

Five ways the same system shows up in front of a customer.

ANY CATALOG

The storefront answers in sentences

Shoppers describe occasion, fit, and budget in their own words. The system resolves all of it at once and replies with products that clear every constraint, in stock.

CUSTOMER

Something elegant for a summer gala, walkable, under $400.

ASSISTANT · 3 MATCHES
Rose Garden chiffon maxi$96 · in stock
Emerald Bloom slit gown$151 · in stock
Petal appliqué mini$128 · in stock
ANY IMAGE

Search that has seen the product

Silhouette, material, and color are part of the representation, so "something like this, but different" is an answerable request rather than a dead end. Works the same for sneakers, jewelry, furniture, or art.

"Find me pants like these."

find me pants like these

ASSISTANT

White silk wide leg pants, similar to your outfit:

Silk Wide Leg Trousers$185 · in stock
Satin Pleat Front Pants$142 · in stock
MARKETPLACES · RETAIL

The shelf that moves with the session

Rankings adapt to live behavior while campaigns, priorities, and inventory constrain every decision. The business stays in the loop, automatically.

"Show me something similar, but under $200."

RANKING · LIVE SESSION
01Fold flat jacket
02Trail shellcampaign
03Commuter parka
04Rain jacketlow stock
CUSTOMER SERVICE

Support that knows the order

After the purchase: returns, exchanges, order status, and warranty questions. The support conversation reads the same customer, order, and policy state as shopping, so it answers from the actual order instead of a script, and can suggest the right next purchase in the same reply.

"Can I return this in store if I bought it online?"

ORDER #48120 · DELIVERED
Linen two piece set$150 · size M
ASSISTANT

Yes. In store or by mail until October 2. Your size in ivory is also back in stock.

EMERGING · AGENTS

Built for buyers that are not people

When an agent shops on a customer's behalf, it issues constraints, not keywords, and expects structured, grounded answers at machine speed. That is the native workload.

"Best option, all constraints, before Friday."

AGENT REQUEST

constraints: garden wedding · maxi · under $250 · by Fri

STRUCTURED ANSWER · 3.4 S
Floral halter maxi$150 · arrives Thu
Floral wrap maxi$185 · arrives Fri

Commerce is multimodal by nature

An image. A material. A silhouette. A color. A specification. A price. A use case. A set of relationships to other products.

Image Text Attributes Behavior Business state
Your commerce
model

Your store gets a brain in three steps

Install, train, go live

01
Install the pixelOne line of code. Views, clicks, carts, purchases.
02
Celeris trains your modelAutomatic. Your products and shoppers become one representation. Yours only.
03
Go live where customers areCommercial rules inside every decision.
<script src="celeris.ai/pixel"></script>
✓ installed

That is the whole integration.

<script src="celeris.ai/pixel"> ✓ installed CAPTURED 0
Rose chiffon maxi$96
Green halter$139
Emerald slit gown$151
ONE REPRESENTATION · CATALOG-V3
IMAGES
TEXT
Rose Garden chiffon maxi. Halter neckline, ruffle hem, hidden zip. Lined, true to size.
ATTRIBUTES blushgardenmaxichiffonwedding guest
BEHAVIOR
viewed 2,114 · carted 302 · bought 88
found via "summer gala dress"
DEDICATED
SERVES ONLY
YOUR BUSINESS
SURFACES
Search
Recommendations
Conversation
Personalization
Support
Agents
garden wedding, maxi, under $160

Three that fit, all in stock:

Floral maxi$150
Green halter$139
Rose chiffon$96
the green one, but in petite?

In stock in petite, arrives Thursday. A campaign price applies at checkout.

Ask anything|
ONE MODEL ACROSS EVERY CUSTOMER SURFACE
Conversational commerce●Intelligent storefronts●Search●Personalization●Recommendations●Post-sale support●Agent traffic● Conversational commerce●Intelligent storefronts●Search●Personalization●Recommendations●Post-sale support●Agent traffic●

The fastest AI model behind all of it

Built for production commerce

Real catalogs, live inventory, high interaction volume. Below, the same answer generated by both systems at their measured production rates. Not sped up.

CELERIS-1 · 1,664 TOK/S0.00 s
A GENERAL AI MODEL · 20 TOK/S0.00 s

Frequently asked questions

Customer interactions across ecommerce search, recommendations, personalization, conversational shopping, customer service, and emerging commerce agent experiences.
A language model understands the interaction. A commerce system also requires access to products, customer context, behavior, inventory, business state, and commercial constraints. Celeris brings those systems together inside the interaction.
A single customer interaction can require multiple model calls, retrieval operations, decisions, and tool calls. Latency compounds across the complete trajectory. For systems operating while a customer waits, model latency becomes part of the product experience.
Yes. Celeris for Commerce is designed to operate with existing commerce data and systems rather than requiring every part of the environment to be replaced.
No. Celeris builds the intelligence layer, not a storefront or a checkout. We do not own catalogs, take a share of transactions, or sit between you and your customers. Your catalog, your data, and your customer relationships stay yours.

See your store think

We run Celeris on your actual catalog, and you watch it answer the questions your customers ask every day.

30 minutes.

Request received.

We will be in touch within one business day.