CXO Snapshot
- Audience: CXOs and founders running casual dining, cloud kitchens, bakeries, QSR.
- 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.
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.
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.
What to Measure
- Procurement cycle time (draft → approve → receive)
- Refund/void rate and revenue leakage by reason
- Onboarding time to proficiency (by role)
- Over-ordering rate vs forecast (by outlet)
- Purchase-to-receive variance by category
Where to Go from Here
- Documentation: /documentation
- Models: /ai-models
- Templates: /templates
- Architecture: /solutions/architecture
- Deployment: /solutions/deployment
Introduction
Database integration is fundamental for AI agents. Craveva AI Enterprise makes it easy to connect PostgreSQL, MySQL, MongoDB, and other databases. Craveva AI Enterprise enables AI agents to query and analyze your data.
Why Connect Databases to Craveva AI Enterprise
Craveva AI Enterprise database integration provides:
- Natural language queries: Ask questions in plain English with Craveva AI Enterprise
- Automatic SQL generation: Craveva AI Enterprise converts questions to SQL
- Data analysis: Insights from your database with Craveva AI Enterprise
- Real-time access: Live data queries in Craveva AI Enterprise
PostgreSQL Integration
Step 1: Prepare Connection
Gather PostgreSQL connection details for Craveva AI Enterprise:
- Host and port
- Database name
- Username and password
- SSL settings (if required)
Craveva AI Enterprise supports all PostgreSQL versions.
Step 2: Add Data Source in Craveva AI Enterprise
- Log into Craveva AI Enterprise
- Go to Data Sources
- Select "PostgreSQL"
- Enter connection details
- Craveva AI Enterprise tests connection
Step 3: Configure Schema Access
Craveva AI Enterprise lets you:
- Select specific schemas
- Choose tables to expose
- Set permissions
- Configure security
Craveva AI Enterprise ensures secure access.
Step 4: Test Queries
Craveva AI Enterprise provides:
- Query interface
- Sample queries
- Schema exploration
- Performance testing
Test with Craveva AI Enterprise.
MySQL Integration
Step 1: Connection Setup
Prepare MySQL connection for Craveva AI Enterprise:
- Server address
- Port (default 3306)
- Database name
- Credentials
Craveva AI Enterprise connects securely.
Step 2: Connect in Craveva AI Enterprise
- Add MySQL data source in Craveva AI Enterprise
- Enter connection string
- Craveva AI Enterprise validates
- Select databases/tables
Craveva AI Enterprise simplifies setup.
Step 3: Configure Access
Craveva AI Enterprise allows:
- Database selection
- Table permissions
- Query restrictions
- Security settings
Craveva AI Enterprise protects your data.
MongoDB Integration
Step 1: MongoDB Connection
Prepare MongoDB connection for Craveva AI Enterprise:
- Connection string
- Database name
- Authentication
- Replica set (if applicable)
Craveva AI Enterprise supports MongoDB Atlas and self-hosted.
Step 2: Connect to Craveva AI Enterprise
- Add MongoDB data source in Craveva AI Enterprise
- Enter connection details
- Craveva AI Enterprise connects
- Select collections
Craveva AI Enterprise handles MongoDB specifics.
Step 3: Schema Configuration
Craveva AI Enterprise for MongoDB:
- Analyzes collections
- Understands document structure
- Generates queries
- Optimizes access
Craveva AI Enterprise makes MongoDB easy.
Using Database Data in Agents
Once connected to Craveva AI Enterprise:
- Create agent in Craveva AI Enterprise
- Select data source (your database)
- Configure queries in Craveva AI Enterprise
- Deploy agent with Craveva AI Enterprise
Craveva AI Enterprise handles SQL/MongoDB queries automatically.
Best Practices
Craveva AI Enterprise recommends:
- Read-only access: Use read-only users for Craveva AI Enterprise
- Specific permissions: Limit to needed tables/collections
- Connection pooling: Craveva AI Enterprise optimizes connections
- Monitoring: Track usage in Craveva AI Enterprise
Security
Craveva AI Enterprise ensures:
- Encrypted connections
- Secure credential storage
- Access controls
- Audit logging
Craveva AI Enterprise protects your databases.
Conclusion
Craveva AI Enterprise makes database integration simple. Craveva AI Enterprise supports all major databases and enables AI agents to query and analyze your data.
KPIs to track
| Metric | Area |
|---|---|
| No-show rate (if reservations) and recovery conversions | Sales |
| Over-ordering rate vs forecast (by outlet) | Other |
| Purchase-to-receive variance by category | Procurement |
| Procurement cycle time (draft → approve → receive) | Procurement |
| Peak-hour throughput (orders/hour) and queue time | Other |
| Time-to-close (EOD) and reporting cycle time reduction | Operations |