Inventory & buying
Turn sales, on-hand inventory, aging, and vendor data into a review queue for reorder, hold, markdown, and expiry decisions.
Retail decisions, grounded in your data
Know what needs attention before it costs you.
Waves turns cannabis retail data into a daily operating system for buying, inventory, pricing, team performance, and demand planning.
Built for operators who need auditable answers, not another static dashboard.
One workspacePOS, inventory, catalog, and market context
Decision-readyExceptions and actions before vanity metrics
Human-reviewedOperators approve the work that moves forward
The platform
From fragmented reports to one operating rhythm.
Waves keeps each decision tied to its source, period, and freshness so your team can move quickly without hiding uncertainty.
Store operations
See traffic patterns, closing reports, customer lifecycle signals, and team performance without rebuilding the same spreadsheet every week.
Market pricing
Compare your live assortment with nearby menus by category and package size, with clear source and freshness notes.
Demand planning
Keep forecasts, actuals, and forecast error together so operators can see where demand is moving and where the model missed.
Ask Waves
Go from question to governed answer.
Ask a plain-language question across supported operational data. Waves builds the answer from controlled, read-only analysis and shows the source and scope behind it.
Which products need a buying decision today?Where are discounts growing faster than sales?What changed versus the prior four weeks?
Ask WavesRead-only
Where should I investigate first?
Start with the exceptions that combine low cover with recent demand.
The buying queue separates immediate review from watch items, then links back to the exact source view.
Source: Inventory & Buying · scope and freshness shown in appHow it works
Trust the path from source to decision.
- 01
Connect
Bring governed POS, inventory, catalog, and public menu data into one operating view.
- 02
Reconcile
Surface missing costs, stale inputs, unmatched products, and source differences before they distort a decision.
- 03
Decide
Review prioritized exceptions, ask follow-up questions, and export the approved work—not a black-box recommendation.
Built for real operating detail
Move from the summary to the row that explains it.
Filter by period, employee, category, vendor, product, or review state. Keep aggregate signals close to the underlying work your team needs to inspect.
- Explicit source and period labels
- Search, filters, and export-ready review states
- Role-aware access to internal workflows
Names and operating data blurredData trust
Designed to make uncertainty visible.
Read-only intelligence
Analysis stays separate from source systems. Buying actions remain reviewable and operator-controlled.
Freshness in context
Source periods, verification times, and limitations appear with the metric instead of disappearing into a footnote.
Role-aware access
Authenticated workspaces keep internal operations separate from approved vendor handoffs and public material.
Reconciliation first
Waves surfaces source gaps and mismatches rather than quietly filling them with a plausible answer.
FAQ
Questions operators ask before they add another tool.
Who is Waves for?
Waves is being built for cannabis retail operators who own inventory, buying, merchandising, pricing, and store performance decisions.
What data does it use?
The platform can combine governed POS, catalog, inventory, transaction, and public competitive-menu data. Exact coverage depends on the retailer and source configuration.
Does Waves place orders automatically?
No. Waves can prioritize items and support buying workflows, but operators review and approve decisions before anything moves forward.
Is this a generic business-intelligence dashboard?
No. The product is organized around recurring cannabis retail decisions, with the source, period, freshness, and limitations kept visible.
See Waves with your operating questions