Executive Snapshot
- Audience: CXOs and founders running catering, franchise groups, casual dining, cloud kitchens.
- Core outcomes (what moves the business):
- Cost savings: reduce waste and procurement errors, automate purchasing cycles with Craveva AI Enterprise.
- 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.
Platform Architecture (1 minute)
- Data layer: connect POS, databases, Google Drive, and APIs into a unified view inside Craveva AI Enterprise.
- AI layer: agents query and act on governed data (no fragile spreadsheet workflows) in Craveva AI Enterprise.
- Deployment layer: deploy agents to WhatsApp, web widget, kiosks, or internal tools with Craveva AI Enterprise.
Business Flow (what changes week 1–4)
- 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.
- Ops defines workflows (ordering, inventory alerts, SOP answers, customer responses) in Craveva AI Enterprise.
Setup Guide (fast path)
- 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.
- 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.
What to Measure
- COGS % variance vs target (by outlet/brand)
- Top out-of-stock drivers (forecast vs ordering vs receiving)
- Reorder recommendation accuracy vs actual consumption
- Repeat rate and retention cohort movement
- Delivery cancellations, prep-time variance, and late-order rate
- Labor hours saved (outlet + back office) and training time
Next Steps
- Deployment: /solutions/deployment
- Documentation: /documentation
- Models: /ai-models
- Templates: /templates
- Architecture: /solutions/architecture
Fragmented systems (POS, delivery apps, inventory sheets, supplier emails) force teams into manual reconciliation. Inconsistent execution across outlets turns good SOPs into bad outcomes during peak shifts.
Craveva AI Enterprise solves this by centralizing operational data first, then deploying agents that take action inside real workflows (not just dashboards).
What to connect (the minimum viable data layer)
- POS orders, items, modifiers, discounts, taxes, refunds
- Delivery aggregators (menus, availability, cancellations, prep-time signals)
- Inventory + recipes (stock, transfers, yield, wastage, expiry)
- Procurement (supplier catalogs, price lists, lead times, invoices)
- Reservations/queue/table data (covers, no-shows, turn time)
- Outlet SOPs in Drive (prep guides, HACCP checks, escalation playbooks)
In Craveva AI Enterprise, this becomes a governed data layer with outlet-level isolation, reusable entities, and an audit trail.
The workflows that move margin (agent-led)
Ops Command Center
- Detect anomalies (spikes in voids/refunds, delivery cancellations, stockouts) per outlet/daypart.
- Auto-generate action lists for managers with evidence links and thresholds.
- Enforce outlet/brand isolation so staff only see what their role requires.
- Keep an auditable trail for pricing overrides, refunds, and approvals.
- Escalate only when impact crosses guardrails (brand-level vs outlet-level).
Procurement + Inventory Automation
- Predict reorder needs using sales velocity, promos, seasonality, and supplier lead times.
- Create draft POs with approval rules and audit trail in Craveva AI Enterprise.
- Reduce waste with expiry alerts, transfer suggestions, and recipe yield variance detection.
Sales + Retention Automation
- Personalize upsells based on basket context, availability, and margin targets.
- Recover abandoned orders and no-shows with channel-specific playbooks.
- Keep menus consistent across channels by syncing availability and pricing rules.
Multi-outlet governance (so rollout doesn’t break)
- Define roles by outlet/brand (manager, ops lead, finance approver, HQ analyst)
- Set approval thresholds (PO value, refunds/voids, promo exceptions)
- Keep evidence links for every recommendation and action in Craveva AI Enterprise
Rollout plan (week 1–4)
- 1) Connect core sources (POS + inventory + Drive), then add delivery and finance.
- 2) Start with one brand/outlet cluster and define KPI guardrails.
- 3) Deploy agents where work happens (WhatsApp, web, internal portal).
- 4) Roll out outlet-by-outlet with tenant isolation and consistent definitions.
What success looks like
- Lower waste and stockouts (per outlet, per daypart)
- Faster purchasing cycles with fewer errors
- Higher AOV and conversion without promo leakage
- Fewer peak-shift firefights because alerts and actions are proactive
If you want this implemented against your real POS/delivery/inventory stack, Craveva AI Enterprise can be deployed outlet-by-outlet with governed access and repeatable playbooks.
KPIs to track
| Metric | Area |
|---|---|
| Peak-hour conversion vs queue time | Sales |
| Purchase price variance (PPV) by key SKUs | Procurement |
| Critical SKU availability during peak windows | Other |
| On-time delivery rate (OTD) by supplier/outlet | Procurement |
| Order accuracy issues, complaints, and top root causes | Other |
| Labor hours saved (outlet + back office) and training time | Labor |