How NetLife AI Works
Start with simple data drops, prove value fast, and scale to automated, real‑time intelligence—without rip‑and‑replace.
Data Pipelines
Ingest data as it exists today—CSV, email, SFTP, or APIs. We normalize and enrich it (including GRiD, fault rates, and carbon data) to build a live picture of your assets.
Set it once and unlock capabilities automatically: our AI applies proven playbooks for spares optimization, reuse, and ESG reporting without heavy IT projects.
- ✓Fast start: prove impact in 30 days
- ✓Automated refresh from ERP/warehouse systems
- ✓API‑first as you scale; continuous data quality checks
1. Quick Start (Weeks 1–4)
Accept data where it is: CSV, email, SFTP. Import snapshots, auto-enrich with GRiD codes. Quick win: identify surplus matching backorders within 30 days.
2. Automate (Weeks 5–8)
Deploy scheduled exports from ERP/warehouse. Stakeholder training and data quality protocols.
3. API Integration (Weeks 9–16)
TM Forum API connectors for real-time sync. Pilot operations, validate AI recommendations, measure impact.
4. Full Optimization (Month 4+)
Automated decision workflows, scale across OpCos/regions. Self-optimizing platform embedded in operations.
GRiD: Digital Asset Identity
GRiD is a digital product passport—a universal identifier encoding technical, functional, and environmental attributes for every part across OEMs and models.
It powers safe interchangeability, traceability, and circular market opportunities so you can redeploy with confidence instead of buying new unnecessarily.
- ✓Vendor‑agnostic catalog and equivalent matching across OEMs
- ✓Part‑level carbon tracking and compliance
- ✓Proven pilots: 60%+ CO₂ reduction, 62% fewer SKUs, 55% lower costs
Reduction in CO₂ emissions
Fewer SKUs to manage
Lower costs
Results from pilot partnership with Safaricom and GSMA
AI Agents
Intelligent agents turn questions into actions—resolving spares, accelerating reuse, and surfacing insights in seconds.
- Spares Optimization Agent: Recommends min/max levels; matches backorders to available or circular stock
- Circularity Agent: Identifies reuse/resell/refurbish options and CO₂e avoided per event
- Infinity Agent: Cross‑checks multiple sources for complete, explainable answers
- Example query: "Find safe alternatives for my top 10 backorders across OEMs."
Conversational Interface: Ask questions in natural language and get instant, actionable answers.
Multi-Source Intelligence: Agents query across inventory, installed base, testing data, and circular stock simultaneously.
Explainable AI: Every recommendation includes reasoning and data sources for full transparency.
Continuous Learning: Agents improve over time as they learn from your network patterns and decisions.
Predictive Intelligence
Predictive and proactive analytics spotlight opportunities and risks—so you act before issues affect uptime or budget.
- ✓Failure risk forecasts by part and site with early‑warning alerts
- ✓Modernization and replacement prioritization to reduce outages
- ✓Stocking recommendations to hit 95%+ service levels with less inventory
- ✓Business‑ready notifications integrated with your workflows
Risk Scoring: Every part and site gets a risk score based on age, fault history, and lifecycle tier.
Early Warnings: Automated alerts when equipment approaches end-of-support or shows elevated fault patterns.
Optimization Recommendations: AI suggests which sites to modernize first, which parts to stock, and where to redeploy idle assets.
Impact Forecasting: See projected cost, uptime, and carbon impact of different scenarios before you commit.