Introducing Agentic AI Platform

Agentic Commerce

Personalize commerce journeys with AI agents that can sell and serve

Guide shoppers from discovery to purchase with recommendations, cart recovery, order tracking, support, and personalized upsell workflows.

Right-click and drag across the canvas to disperse particles.

What it does

Commerce teams lose revenue when discovery, support, order status, and retention live in separate systems. Production commerce agents need catalog rules, customer context, payment safety, and merchandising controls.

Who it is for

For retailers, marketplaces, subscription brands, B2B commerce teams, and digital sales organizations.

Key Capabilities

Composable capabilities designed for real deployment, continuous improvement, and secure enterprise operations.

Product discovery

Built as an enterprise-ready capability with measurable operational value.

Recommendations

Built as an enterprise-ready capability with measurable operational value.

Cart recovery

Built as an enterprise-ready capability with measurable operational value.

Customer support

Built as an enterprise-ready capability with measurable operational value.

Order tracking

Built as an enterprise-ready capability with measurable operational value.

Upsell and cross-sell

Built as an enterprise-ready capability with measurable operational value.

Architecture Modules

A modular deployment model gives technical teams flexibility while giving executives a clean operating view.

01
Catalog understanding
02
Recommendation rules
03
Cart recovery
04
Order support
05
Returns guidance
06
Lifecycle campaigns

Production intelligence layer

Advanced operating data for deploying Agentic Commerce with measurable performance, clear release paths, and enterprise controls.

Catalog rules
Real-time

Recommendations can respect inventory, eligibility, region, margin, and merchandising policy.

Journey coverage
Pre + post

Product discovery, cart, checkout support, order tracking, returns, and loyalty.

Revenue signals
Tracked

Attribute recovered carts, assisted conversions, upsells, support deflection, and repeat purchase.

Reference architecture

Catalog connector

Read product, price, inventory, promotions, variants, and merchandising constraints.

Customer context

Use approved profile, order, loyalty, and browsing signals to personalize safely.

Commerce action layer

Recover carts, check order status, start returns, create support tickets, and trigger campaigns.

Revenue analytics

Measure conversion, AOV, support deflection, cart recovery, and post-purchase engagement.

Production release path

1Catalog and policy sync
2Journey mapping
3Promotion guardrails
4Pilot storefront
5Revenue attribution tuning

Enterprise controls

Merchandising rulesPayment boundariesInventory constraintsReturn policy citationsOffer approvalCustomer data limits

Benefits

The platform is designed around outcomes leaders can measure, govern, and communicate.

Increase conversion
Recover abandoned carts
Reduce commerce support load
Personalize at scale

Example User Journeys

Representative workflows show how agents move from insight to action across real systems.

Understand shopper need
Recommend products
Answer questions
Recover cart
Track order
Suggest next purchase

Technical Architecture

Security, observability, approvals, and auditability are designed into the operating model from the beginning.

Catalog connector

Configured for secure deployment, measurable performance, and governance review.

Recommendation engine

Configured for secure deployment, measurable performance, and governance review.

Conversation agent

Configured for secure deployment, measurable performance, and governance review.

Order system

Configured for secure deployment, measurable performance, and governance review.

Marketing automation

Configured for secure deployment, measurable performance, and governance review.

Integrations

Connect AI agents to the systems where work, knowledge, customer context, and approvals already live.

ShopifyMagentoCommerce CloudKlaviyoStripeZendesk
42%

average reduction in manual workflow time

99.9%

target platform availability for enterprise deployments

10x

faster agent rollout with reusable orchestration modules

24/7

AI operations across channels, teams, and regions

Customer Confidence

Enterprise buyers need proof that AI systems can create value without increasing operational risk.

The platform gave our operations teams a governed way to deploy AI agents without losing control of data, workflows, or compliance.
Maya Chen
Chief Digital Officer, Global Services Group
We moved from pilot projects to measurable automation outcomes across support, knowledge search, and internal engineering workflows.
Arun Malik
VP Infrastructure, CloudScale Telecom
The security model and observability layer made it possible to bring legal, IT, and business leaders into the same deployment motion.
Elena Brooks
Head of Enterprise AI, Northstar Financial

FAQ

Common questions from technical evaluators, business sponsors, and governance teams.

Can recommendations use catalog rules?+

Yes. Recommendations can respect stock, margin, geography, eligibility, and merchandising rules.

Can it support post-purchase journeys?+

Yes. Agents can handle order status, returns, support, replenishment, and loyalty journeys.

Ready to build enterprise AI systems that move from pilot to production?

Book a working session with our AI architects to map use cases, data readiness, infrastructure needs, and deployment priorities.