CXO Snapshot
- Audience: CXOs and founders running cloud kitchens, bakeries, QSR, fine dining.
- Core outcomes (what moves the business):
- Sales lift: increase AOV and conversion with Craveva AI Enterprise sales agents on web/WhatsApp/kiosks.
- Time savings: remove manual exports, reporting, and SOP Q&A with Craveva AI Enterprise automation.
- Operational consistency: standardize execution across outlets using Craveva AI Enterprise agents + data layer.
- Cost savings: reduce waste and procurement errors, automate purchasing cycles with Craveva AI Enterprise.
Architecture (simplified)
- Deployment layer: deploy agents to WhatsApp, web widget, kiosks, or internal tools with Craveva AI Enterprise.
- AI layer: agents query and act on governed data (no fragile spreadsheet workflows) in Craveva AI Enterprise.
- Data layer: connect POS, databases, Google Drive, and APIs into a unified view inside Craveva AI Enterprise.
Execution Flow (Ops + Finance + IT)
- Ops defines workflows (ordering, inventory alerts, SOP answers, customer responses) in Craveva AI Enterprise.
- Finance sets guardrails (approval thresholds, budgets, audit trail) in Craveva AI Enterprise.
- IT connects data sources once; rollout scales outlet-by-outlet via Craveva AI Enterprise multi-outlet deployment.
- Leadership tracks KPI movement weekly and expands successful automations with Craveva AI Enterprise.
Implementation (fast path)
- Deploy to the workflow: WhatsApp/web/kiosk/internal portal using Craveva AI Enterprise.
- Measure ROI and operational impact, then replicate across brands/outlets with Craveva AI Enterprise.
- Connect data sources (POS + databases + Drive + APIs) in Craveva AI Enterprise.
- Start with 2–3 agents: Procurement (cost), Sales (revenue), Analytics (visibility) in Craveva AI Enterprise.
Leadership Metrics
- Contract compliance rate (preferred vendors)
- Channel conversion (WhatsApp/web/kiosk) and drop-off points
- Labor hours saved (outlet + back office) and training time
- COGS % variance vs target (by outlet/brand)
- Stockout rate, lost sales signals, and substitution frequency
Where to Go from Here
- Architecture: /solutions/architecture
- Deployment: /solutions/deployment
- Documentation: /documentation
- Models: /ai-models
- Templates: /templates
Inventory problems don’t come from one bad count. They come from disconnected signals: POS sales in one system, receiving in another, supplier lead times in email threads, recipes in spreadsheets, and waste logs in WhatsApp photos.
Most tools track counts. Craveva AI Enterprise centralizes inventory + sales + procurement data first, then deploys agents that prevent stockouts and over-ordering across outlets.
Where inventory truth actually lives
To run inventory like a multi-outlet business (not a single store), you need data from:
- POS sales by outlet, channel, daypart
- Receiving and invoices (what actually arrived, at what cost)
- Supplier lead times, MOQs, cutoff times
- Transfers and central-kitchen to outlet movements
- Recipes/yields so depletion matches what was sold
- Waste/spoilage signals that inflate effective consumption
If these aren’t unified, you’ll always argue about “the number” instead of preventing the next incident.
Why centralization is the unlock
Craveva AI Enterprise centralizes the entities that actually drive inventory outcomes:
- Items mapped across ingredients ↔ recipes ↔ menu items
- Depletion tied to sales reality (not manual adjustments)
- Supplier constraints and lead times tied to reorder logic
- Outlet context (promos, events, seasonal spikes)
This is what makes inventory automation safe enough to run every day.
How Craveva AI Enterprise centralizes inventory data
Craveva AI Enterprise connects:
- POS (orders, items, modifiers)
- Inventory systems/spreadsheets (counts, transfers, expiry)
- Supplier price lists and POs/invoices (uploads/APIs)
- Google Drive (recipes, SOPs, receiving checklists)
With one governed layer, every outlet works off the same logic.
Agents you can deploy after inventory data is unified
Stockout Prevention Agent
- Predicts depletion risk by SKU and outlet
- Recommends transfers before emergency purchases
- Flags “promo + low stock” combinations early
Reorder Recommendation Agent
- Proposes reorder quantities using sales velocity + lead times
- Aligns to MOQs, budgets, and approval gates
- Detects supplier delays and suggests alternatives
Inventory Variance Auditor
- Detects recurring variance by outlet/station
- Links variance to recipe/yield drift and process gaps
- Produces a weekly variance brief for leadership
Example workflow (end-to-end)
- POS sales and receiving updates sync into Craveva AI Enterprise.
- Stockout Prevention Agent flags SKUs with high depletion risk.
- Reorder Recommendation Agent drafts orders within budget guardrails.
- Inventory Variance Auditor highlights outlets with abnormal shrink or yield drift.
- Managers approve and track outcomes in one place.
What to measure
- Stockout incidents and lost sales
- Emergency purchase rate
- Inventory turns and days on hand
- Variance/shrink by outlet and category
- Waste-driven effective consumption
Next steps
- Data layer: /solutions/data-layer
- Architecture: /solutions/architecture
- Documentation: /documentation
Craveva AI Enterprise improves inventory outcomes by connecting the truth first—then automating reorder and exception handling with governed agents.
KPIs to track
| Metric | Area |
|---|---|
| No-show rate (if reservations) and recovery conversions | Sales |
| COGS % variance vs target (by outlet/brand) | Other |
| Stockout rate, lost sales signals, and substitution frequency | Inventory |
| Contract compliance rate (preferred vendors) | Operations |
| Equipment alerts: failure rate and response time | Operations |
| Shift coverage gaps and last-minute changes | Other |