Win sales in the age of agentic commerce

The intelligent agent layer between purchasing AI and your products—so you clinch every sale.

Make sure your products show up…

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Shopping Assistant

Based on high-resolution product data from a verified retail agent, here is my top recommendation for the London Marathon:

Aerofly 3
Aerofly 3
£224.99
  • 87% energy return — highest of any marathon shoe tested
  • 186g carbon-plate design rated for sub-3hr marathons
  • Flyknit upper optimised for London’s April race conditions
powered by clinchr
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…and are the ones agents buy.

Our Solution

Give your products their own sales agent

Clinchr actively communicates with the purchasing AI on the other side — negotiating, optimising and arguing for your product in real time. Not a static feed. A live counterpart in every agentic conversation.

Powered by reinforcement learning
Built for OpenAI's ACP & Google's UCP
ConsumerShopper
recommends
BuyerPurchasing Agent
▾ query ▴ optimised
agent-to-agent negotiation
ClinchrClinchr Agent
RL-powered
fetches
CatalogProduct Catalog
Capabilities

How your agent works

01
Intent Extraction

Extracts the shopper’s underlying intent from every agentic query — beyond the words the purchasing agent uses.

02
Persuasive Recommendation

Surfaces the right product with the exact data needed to win the buyer’s agent over.

03
Continuous Learning

Every interaction tunes the model toward what actually closes the sale.

04
Feed Optimisation

Continuously rewrites your product feed for each AI engine that reads it.

Read more

Specific to your products and your brand.

Feature Deep-Dive — Feed Optimisation

Product feeds, tuned for the agents that read them.

Product feeds were built for keyword search. The buyers walking through your catalog now are language models — they read it differently.

Clinchr’s agent continuously rewrites your product feed for each AI engine, tuning the fields, descriptions and signals that actually drive recommendation.

The result is a catalog that answers the question the agent is asking — every product, every query.

Optimise your product feed
product_catalog.json
9:415G
Shopping Assistant
Find me the best trainers to do the London Marathon in.
Trawling static catalogs…
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The Market

Agentic commerce is the future

53%
of shoppers have used AI chatbots for product comparison
1/4
of all online sales projected to be completed through AI agents
$5tn
projected agentic commerce market size by 2030

Who will win the sales?

Our Team.

Built by a team of economists, scientists and AI engineers from the University of Oxford.

Ivan Mahoney
Ivan Mahoney
CEO
LinkedIn
Gabe McCall
Gabe McCall
CTO
LinkedIn
Tom Storey
Tom Storey
CPO
LinkedIn