Make your catalog, inventory, and stores AI-agent ready.

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

Shopify
Qonto
Leafworks

The mandate

Turn fragmented commerce data into an agent-ready revenue engine.

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

  • Agent-ready catalog + digital shelf: structured, semantic, permissioned APIs.
  • Inventory, pricing, and promo agents with real-time, policy-aware actions.
  • Merchandising & search copilots that actually understand your assortment.
  • Edge intelligence for in-store experiences, associates, and loss prevention.
  • Agentic checkout & CX: conversational commerce, returns, and post-purchase.
Scope an agent-ready workflow

Why it works

Why this approach wins.

01 · Principle

Your catalog becomes an API agents actually use

Semantic attributes, images, policies, inventory, and pricing exposed with trust signals — so external and internal agents can reason, not guess.

02 · Principle

Merchandisers and CX stop firefighting

Copilots handle bulk setup, PDP hygiene, returns, and routine tickets. Your humans focus on brand, margin, and judgment calls.

03 · Principle

Stores become smart without a rip-and-replace

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

The outcomes we commit to.

+15%

PDP conversion

−40%

CX handle time

merch velocity

−20%

shrink + OOS

Awards

Proud moments.

Top 1% on Clutch Global

Top 1% on Clutch Global

Top AI Strategy Company 2025

Top AI Strategy Company 2025

Clutch Fall Champion 2024

Clutch Fall Champion 2024

Inc. 5000 Fastest Growing

Inc. 5000 Fastest Growing

Breakthrough of the Year 2019

Breakthrough of the Year 2019

Member of Forbes Tech Council

Member of Forbes Tech Council

Voice & Speech Recognition 2024

Voice & Speech Recognition 2024

Top Blockchain Company 2024

Top Blockchain Company 2024

Innovators of the Year 2019

Innovators of the Year 2019

GoodFirms Top Company

GoodFirms Top Company

Pain points

Do you recognize your team?

What's happening

  • ChatGPT, Perplexity, and shopping agents now send real traffic — and you don't know what they see.
  • Merchandising and catalog ops can't keep up with SKU and channel growth.
  • CX volume and handle time are squeezing margin.
  • Store ops still run on spreadsheets and radios.
  • A competitor just shipped conversational commerce on your category.

How it feels

  • Anxious about being disintermediated by AI shopping agents.
  • Frustrated by legacy PIM / OMS / POS stacks that resist modern tooling.
  • Tired of 'AI' vendor demos that don't survive a real assortment.
  • Pressured on margin, on-time delivery, and customer experience at once.
  • Excited by what real-time, store-level intelligence could unlock.

Where it hurts

  • Catalog data that's inconsistent across channels, markets, and locales.
  • Inventory, promos, and pricing updates lagging the customer.
  • Search + recommendations that don't understand synonyms or intent.
  • CX queues drowning in simple, policy-answerable questions.
  • Store data trapped in POS and RFID silos.

What we ship

Workstreams, real artifacts, measurable outcomes.

Every engagement decomposes into clear workstreams you can ship and measure. Here's the playbook for this segment.

Workstream

01

Agent-ready catalog & APIs

Semantic, permissioned product + policy APIs exposed safely to external and internal agents.
  • Semantic schema
  • Agent-safe API layer
  • Trust + auth
  • Feed observability
AI channel-ready

02

Merchandising & search copilot

Agents draft PDPs, enrich attributes, tune search, and flag assortment gaps at scale.
  • PDP generator
  • Attribute enrichment
  • Search tuning
  • Gap dashboards
3× velocity

03

Pricing, promo & inventory agents

Policy-aware agents for price changes, promo setup, and real-time inventory reasoning.
  • Policy layer
  • Action tools
  • Simulation + rollback
  • Audit log
+ margin control

04

CX, returns & post-purchase

Conversational agent grounded on policy, order, and product — with human escalation built in.
  • Grounded chat
  • Order + returns tools
  • Escalation flow
  • QA + eval set
−40% handle time

05

Store edge intelligence

Real-time agents over POS, RFID, and cameras for ops, LP, and associate enablement.
  • Edge pipeline
  • Associate app
  • LP signals
  • Ops dashboards
−20% shrink + OOS

As seen in

Forbes
The Recursive
SVT
Breakit
Tech EU

After-state

What changes on the other side.

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

ConfidentModernAgent-readyIn control of marginWinning the next channel

What becomes possible

  • 01Turn autonomous commerce into a reliable, measurable revenue channel.
  • 02Make merchandising, CX, and ops scale faster than SKU and order count.
  • 03Stand up store-level real-time intelligence without replacing POS or RFID.

Concerns, answered

The usual concerns — handled.

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

Why us and not…

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

Senior humans,
AI-native craft.

100+

people trained

20+

companies transformed

9.4/10

avg. workshop rating

96%

AI adoption in 7 days

Talk to the founder

Mike Doroshenko

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.

Book a call with Mike
Mike — Founder of Vahue

Delivery outcomes.

Measurable results from products and AI systems delivered by Vahue.

Enterprise AIVahue case study

−27% TTR

Production NOC agents reduced repeatable incident resolution time by 27% while recording zero unauthorized execution in UAT and staging.

Exaware

Enterprise AI

Enterprise AIVahue case study

>90% automated

More than 90% of RFI responses were automated, moving turnaround from several days to a few hours without removing editing or audit history.

Global B2B Growth Partner

Enterprise AI

Enterprise AIVahue case study

Seconds, not hours

Every repair order could be scored in seconds at 75–80% agreement, while costly billing decisions remained behind human-defined confidence thresholds.

Amerit Fleet Solutions

Enterprise AI

Enterprise AIVahue case study

~10% → ~20%

An unstable scheduling voicebot doubled booking conversion from roughly 10% to 20% while becoming faster, less token-heavy, and easier to monitor.

Docplanner

Enterprise AI

AI-Native EngineersVahue case study

8 months → 6+

Five senior data scientists helped bring an eight-month NLP delivery down to just over six months and cleared inherited technical issues in about one month.

Retail NLP Delivery

AI-Native Engineers

AI-Native EngineersVahue case study

>95% accuracy

A classifier exceeded 95% accuracy, integrated through an API within days, and shipped with documentation for retraining on future data.

Consumer Email Startup

AI-Native Engineers

AI-Native EngineersVahue case study

Value from day one

Embedded specialists onboarded quickly and delivered models, workflow pipelines, deployment support, and ongoing production ownership across several business areas.

Sky

AI-Native Engineers

Team Training & ConsultingVahue case study

>30% adoption

The employee assistant reached more than 90% reported answer accuracy and more than 30% company-wide adoption across permissioned CRM and ERP data.

PioGroup

Team Training & Consulting

Team Training & ConsultingVahue case study

Run in-house

A cross-functional pilot, training, and rollout blueprint left the organization able to run, explain, and extend marketing-mix modeling independently.

Global Food Company

Team Training & Consulting

Team Training & ConsultingVahue case study

6-week roadmap

Several focused sessions converted clinical expertise and vendor distrust into a realistic product design, technical stack, cost range, and scalable roadmap.

Clinical Tools Company

Team Training & Consulting

Contact

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Tell us where you are and what you're trying to ship. We reply within 24 hours with a diagnosis, a shortlist of quick wins, and the smallest next step we'd recommend.

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