Onboarding

This guide outlines the onboarding process for implementing Asoba’s AI-powered Operations & Maintenance (O&M) solution for solar energy assets. The process is structured into parallel workstreams—Client, Sales, and Technical—to ensure alignment throughout Proof of Concept (PoC) activation and readiness for full commercial deployment.

1. Overview

The Ona AI-Driven O&M platform transforms solar asset operations through real-time anomaly detection, predictive maintenance, and intelligent fault classification. The onboarding process follows a structured workflow from initial engagement through full commercial deployment, with clear roles and responsibilities for each phase.

Value Proposition

Faster Claims Processing: Reduce revenue loss through accelerated incident identification and resolution
Proactive Maintenance: Shift from reactive cost centers to predictive profit optimization
Unified Data Infrastructure: Eliminate manual ETL and gain cross-asset visibility
AI-Powered Insights: Achieve 7% SMAPE forecasting accuracy and sub-10-minute anomaly detection

2. Onboarding Workflow

Complete onboarding workflow from kickoff to commercial deployment

Week 1

Phase 1: Kickoff

Initial engagement and project initiation
O&M AI model capabilities overview
Stakeholder roles and responsibilities
PoC objectives and timeline
Success criteria definition

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Week 1

Phase 2: Define PoC KPIs

Uptime improvement targets
Fault prediction accuracy thresholds
Cost savings metrics
Revenue optimization goals

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Week 1-2

Phase 3: Data Governance Assessment

Data source inventory (SCADA, EMS, OEM portals)
Data retrieval protocols and access methods
Security requirements evaluation
Historical data availability assessment

Week 2-3

Phase 4: Data Access Setup

Read-only API keys for inverter clouds
Admin panel credentials (where applicable)
VPN or secure tunnel setup
IP whitelisting for Asoba infrastructure

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Week 3-4

Phase 5: Data Mapping & Inventory

SCADA tags and inverter credentials
Site layout and component inventory
Weather data integration
12+ months historical performance data

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Week 4-5

Phase 6: API Integration

Client account setup
Customer and device registration
API key generation
Real-time and batch data feed configuration

Week 5-6

Phase 7: MVP Infrastructure Setup

Automated weather integration (Visual Crossing API)
Asset registry setup
Data pipeline configuration
Dashboard integration

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Week 6-8

Phase 8: Model Activation & Testing

Model training (12+ months data required)
Performance target validation
Forecasting API testing
Fault detection verification

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Week 8-12

Phase 9: Performance Monitoring

Model accuracy and latency tracking
False positive/negative rate monitoring
System uptime and API response times
SNS alert subscriptions

Week 8-12

Phase 10: Performance Calibration

Weekly performance reports
Threshold adjustments
Model retraining with production data
Feature engineering optimization

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Week 13+

Phase 11: Full Commercial Agreement

ROI analysis and performance validation
Commercial pricing finalization
SLA establishment
Operations team training
Production support handoff

3. Onboarding Setup

The data you provide during onboarding enables our AI platform to deliver powerful insights and automation capabilities. By connecting your energy assets and historical performance data, we can:

Predict Energy Production: Forecast solar generation with high accuracy, enabling better grid integration and energy trading decisions
Detect Anomalies Early: Identify equipment faults and performance degradation before they impact revenue, reducing downtime and maintenance costs
Optimize Maintenance: Schedule proactive maintenance based on predictive analytics rather than reactive repairs, maximizing asset uptime
Enable Automated Decision-Making: Use the OODA (Observe, Orient, Decide, Act) workflow to automatically respond to changing conditions and optimize operations
Provide Cross-Asset Visibility: Gain unified insights across your entire portfolio, identifying patterns and opportunities that individual site monitoring cannot reveal

The quality and completeness of your data directly impacts the accuracy and value of these AI-driven capabilities. Our platform works with data from SCADA systems, EMS platforms, OEM portals, and weather services to build comprehensive models of your energy assets.

Want to explore onboarding further? Contact Sales

4. Technical Support

During PoC

Technical Support: support@asoba.co
Sales Contact: Your designated account manager
Documentation: https://docs.asoba.co

Post-Commercial Deployment

Tier 1 Support: 24/7 system monitoring
Escalation: Direct technical engineering support
Regular Reviews: Quarterly business reviews

5. Data Governance & Security

Data Protection

All data transmitted via TLS 1.3
Data at rest encrypted with AES-256
Read-only access to client systems
SOC 2 Type II compliance (in progress)

Performance Disclaimers

Given comprehensive and up-to-date data, Ona AI-Driven O&M identifies anomalies and recommends corrective actions to assist clients in meeting internal plant-availability and performance KPIs. Actual plant performance depends on:

Client’s operational execution
Timely provision of required data feeds
Prompt response to AI alerts
Quality of field technician work

Contact Support

For technical assistance, feature requests, or any other questions, please reach out to our dedicated support team.

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