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Digital commerce AI
AI for the revenue workflow behind your store.
Pure digital sales businesses already live inside platforms like Shopify, BigCommerce, WooCommerce, marketplaces, headless storefronts, email and SMS tools, support inboxes, fulfillment systems, and analytics dashboards. Folium Systems helps connect AI to that revenue process without breaking the platform that already runs the business.
Industry lane
AI for digital commerce teams that live inside platforms.
Digital sellers already run on a dense stack: storefront, product catalog, support inbox, returns, email and SMS, fulfillment, analytics, marketplaces, and finance tools. Folium helps AI improve that revenue process without breaking the platform that already carries the business.
Commerce play
Product catalog cleanup and enrichment
Commerce play
Support assistant with order and policy context
Commerce play
Returns and post-purchase process automation
Commerce play
Retention, campaign, and analytics next-action routing
Revenue loop
Digital sales are not one page. They are a connected operating system.
Folium connects AI to the work around the store: catalog quality, support, returns, fulfillment signals, campaign timing, analytics, marketplaces, and owner decisions.
Storefront
Product discovery, search, content, pricing questions, and customer experience signals.
Catalog
Attributes, descriptions, variants, inventory, images, SEO, merchandising, and cleanup queues.
Orders
Status, fulfillment, shipping exceptions, refunds, replacements, subscriptions, and customer promises.
Support
Approved policies, order context, product facts, escalation rules, and response drafting.
Retention
Customer events, abandoned paths, repeat purchase timing, SMS/email readiness, and offer review.
Analytics
Conversion, support load, fulfillment friction, returns patterns, revenue leakage, and next actions.
Commerce graphs
Commerce AI should improve revenue operations without bypassing control.
Digital sellers need charts that connect AI to catalog quality, support load, returns, retention, analytics, and platform actions with human review in the path.
Commerce revenue loop
Folium routes AI into the operating loop behind the store: catalog, support, returns, retention, analytics, and approved platform actions.
- 01 Signals
Catalog, search, support, orders, returns, campaigns, and analytics.
- 02 Queue
AI drafts, classifies, enriches, summarizes, and recommends.
- 03 Review
People approve refunds, promises, discounts, product changes, and customer messages.
- 04 Action
Approved work moves into Shopify, BigCommerce, support, email, SMS, or ops.
- 05 Learning
Outcomes improve catalog cleanup, support training, retention, and operations.
Commerce AI control map
AI can support revenue only when risky customer-facing changes remain reviewable.
Safe Classify and summarize
Support tickets, return reasons, catalog gaps, and product issues.
Review Draft customer responses
Use approved policies and order context with human approval.
Review Recommend offers
Suggest discounts, replacements, or follow-up timing for owner review.
Blocked Silent live changes
No unapproved refunds, promises, price changes, or customer messaging.
Process diagram
From platform data to revenue action, with review before live change.
The right commerce AI path does not let an agent silently publish, refund, discount, promise, or message customers. It builds a queue of record-backed work and gives people control over what moves.
Commerce operating loop
AI improves the store by entering the review queue, not by bypassing it.
The loop protects customer experience while still turning platform data into revenue action.
- 01 Store signals Catalog, orders, tickets, returns, fulfillment, campaigns, analytics, and marketplace events.
- 02 AI work queue Agents draft, classify, summarize, enrich, route, and recommend without silently changing the store.
- 03 Owner review People approve customer promises, refunds, discounts, published content, and high-risk changes.
- 04 Platform action Approved work moves through Shopify, BigCommerce, marketplace, support, email, SMS, or operations tools.
- 05 Revenue learning Outcomes feed cleanup queues, support training, retention timing, merchandising, and next experiments.
Commerce revenue agent pack
Agents for the revenue work behind the storefront.
Commerce teams do not need a chatbot floating beside the store. They need AI connected to catalog quality, order context, returns, support, retention, analytics, and operations signals.
Catalog agent
Detect missing attributes, weak descriptions, duplicate products, SEO gaps, and merchandising cleanup needs.
The team gets a prioritized cleanup queue with product fields, owners, and review notes before publishing.
Support agent
Draft grounded responses using order status, policies, product facts, and escalation rules.
Responses stay tied to approved sources while exceptions, refunds, replacements, and promises route to people.
Returns agent
Route return reasons, policy exceptions, replacement offers, and customer experience signals.
Return patterns become operational records for catalog fixes, support training, and retention moves.
Retention agent
Turn customer events into next actions for email, SMS, support follow-up, or offer review.
The process recommends timely next actions without silently sending campaigns or offers without approval.
Analytics agent
Summarize revenue, conversion, support, and fulfillment signals into operator actions.
Owners see what changed, why it matters, which metric needs attention, and what record supports the move.
Ops agent
Watch platform tasks, integrations, content queues, and recurring back-office commerce work.
Daily operations become a monitored queue with exceptions, blockers, ownership, and escalation visibility.
What Folium builds
A commerce AI layer that supports the platform instead of fighting it.
Start with a commerce AI revenue audit, then test one process using sandboxed or redacted store data.
Make the store smarter
We connect AI to product data, customer questions, order context, and content operations so the customer experience improves without a platform rebuild.
- Shopify and BigCommerce AI integration review
- Product discovery and shopping assistants
- Product catalog intelligence and cleanup
- Commerce support with order context
Operate the revenue loop
AI can help the back half of commerce too: retention, returns, fulfillment signals, analytics, multi-channel operations, and next-action processes.
- Abandoned cart and retention automation
- Returns and post-purchase processes
- Commerce event and analytics layer
- Marketplace and multi-channel operations AI
Sandboxed case study
Commerce AI that improves the revenue workflow, not just the chat widget.
Pure digital sales businesses often have scattered catalog, support, fulfillment, marketing, and analytics signals. Folium turns those signals into controlled AI workflows that protect customer experience while improving revenue operations.
Catalog intelligence
Find weak product titles, missing attributes, duplicate listings, poor descriptions, and merchandising cleanup opportunities.
Support acceleration
Prepare draft answers, policy references, order-context summaries, and escalation notes without letting AI make unsupported promises.
Conversion recovery
Map abandoned paths, product confusion, search gaps, pricing questions, and customer objections into testable improvements.
Operations visibility
Connect store events, fulfillment status, support signals, and campaign context into a clearer owner dashboard.
Commerce recovery workflow
Revenue recovery starts by turning scattered store signals into reviewed action.
The commerce path connects the platform data, chooses the first friction point, builds a safe work queue, keeps people over customer-impacting action, and feeds learning back into the store.
- 01 Collect signals Bring together catalog gaps, support tickets, returns, fulfillment, abandoned paths, and analytics.
- 02 Prioritize friction Choose the revenue workflow where AI can reduce rework, confusion, leakage, or customer wait.
- 03 Build safe queue Let AI draft, classify, enrich, summarize, and recommend without publishing or messaging alone.
- 04 Approve action Keep humans over refunds, discounts, promises, product changes, and customer-sensitive moves.
- 05 Feed learning Use outcomes to improve catalog cleanup, support training, retention timing, and operations.
Safe review pattern
Start with sandboxed or redacted store events before touching live commerce systems.
Folium can model the commerce process using approved sample orders, sample products, redacted tickets, and synthetic analytics patterns. The review shows where AI belongs and where human review must stay. Only after the record is clear should the work move toward live API integration, customer data handling, retention rules, and platform governance.
Catalog issue map
Find weak titles, missing attributes, duplicate products, stale descriptions, and merchandising gaps.
Support response boundaries
Define what AI can draft, what sources it may cite, and when a human must handle the customer.
Commerce event model
Connect orders, tickets, returns, fulfillment, campaigns, and analytics into a usable action layer.
Revenue opportunity shortlist
Prioritize the first workflows that can lift conversion, reduce rework, or improve customer experience.
Escalation and review rules
Show where refunds, promises, replacements, exceptions, or high-value customers require approval.
Live API approval checklist
Name the platform permissions, data handling, rate limits, testing, rollback, and owner signoffs.
Review Point
Catalog, support, and revenue operations share context.
Folium packages this as visible review material so owners, staff, and reviewers can decide whether to refine, launch, pause, or expand.
Review Point
AI supports the platform instead of fighting it.
Folium packages this as visible review material so owners, staff, and reviewers can decide whether to refine, launch, pause, or expand.
Review Point
Commerce teams get better signals and faster execution.
Folium packages this as visible review material so owners, staff, and reviewers can decide whether to refine, launch, pause, or expand.
Start here
Digital sales teams need more than another plugin.
Folium helps connect AI to the revenue workflow behind the store: catalog, support, fulfillment, returns, analytics, and operations.
- 01 Scope
- 02 Build
- 03 Prove
- 04 Operate