−27% TTR
Production NOC agents reduced repeatable incident resolution time by 27% while recording zero unauthorized execution in UAT and staging.
We modernize retail stacks so agents — yours and your customers' — can safely read inventory, catalog, pricing, and logistics in real time, and turn commerce into a reliable autonomous channel.
From agent-ready digital shelves and APIs to edge intelligence in stores, and from merchandising and search copilots to agentic checkout — architected for scale, security, and the coming world where AI does the shopping.
Trusted by teams at
The mandate
The next channel isn't another storefront — it's autonomous agents transacting on behalf of shoppers and operators. We modernize the foundations: product, inventory, pricing, promos, logistics, and store data — so external AI agents can discover, trust, and act on them, while internal copilots lift merchandisers, CX, and ops.
What you get
Why it works
01 · Principle
Semantic attributes, images, policies, inventory, and pricing exposed with trust signals — so external and internal agents can reason, not guess.
02 · Principle
Copilots handle bulk setup, PDP hygiene, returns, and routine tickets. Your humans focus on brand, margin, and judgment calls.
03 · Principle
Edge agents layer on top of existing POS, RFID, and cameras — turning each store into a real-time data product for ops, LP, and experience.
Outcomes
+15%
PDP conversion
−40%
CX handle time
3×
merch velocity
−20%
shrink + OOS
Awards
Pain points
What's happening
How it feels
Where it hurts
What we ship
Every engagement decomposes into clear workstreams you can ship and measure. Here's the playbook for this segment.
01
Agent-ready catalog & APIs
02
Merchandising & search copilot
03
Pricing, promo & inventory agents
04
CX, returns & post-purchase
05
Store edge intelligence
As seen in
After-state
Your catalog, inventory, and pricing are exposed as first-class APIs external agents can trust. Merchandising, search, and CX ship with copilots. Stores stream real-time signal to ops and LP. New channels — including AI shopping agents — plug in without another rebuild.
How it feels
What becomes possible
Concerns, answered
Concern 01
“Our PIM / OMS / POS stack is too legacy to touch.”
We wrap, don't replace. Agent-ready APIs and semantic layers sit on top of what you have; we modernize on a runway instead of a big-bang program.
Concern 02
“Exposing product data to AI agents sounds risky.”
We ship permissioned, auditable agent APIs with rate limits, trust signals, and abuse detection. You control who sees what and prove it later.
Concern 03
“We already have search / recsys / CX vendors.”
Good — we layer on them. We target the workflows they leave weak: attribute quality, policy reasoning, long-tail CX, and merchandiser-side automation.
Concern 04
“We don't believe AI shopping agents will move real revenue.”
Maybe not tomorrow — but being readable to them is free upside and near-term SEO + discoverability gains. The cost of not being agent-ready grows every quarter.
Alternatives
Horizontal commerce platforms
Great at storefronts, thin on agent-readiness and cross-system automation.
Search / recsys point vendors
Tune one surface; leave the catalog, policy, and CX agent problem untouched. We connect the dots.
In-house modernization programs
Often stall on legacy cores. We bring senior AI-native engineers who ship around them.
Founder & team
100+
people trained
20+
companies transformed
9.4/10
avg. workshop rating
96%
AI adoption in 7 days
Talk to the founder
Product strategist and AI consultant with 10+ years of digital product strategy and AI transformation. Author of corporate training programs used by leading companies.
Supported by 15+ experts
from McKinsey, Google, and top tech companies.

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