Sono provides a continuous, agent-based risk scoring platform for data center portfolios, tracking live changes in grid capacity, climate exposure, compliance, and equipment health. It converts real-time operational and external data into financial impact projections, enabling investors, operators, and insurers to price risk the day it moves. The platform also delivers predictive maintenance recommendations with confidence scores, extending asset life and reducing carbon footprint.
Funding
Funding not disclosed
Founders
Product
Problem
Data center assets are typically risk-scored only at discrete points—at construction, acquisition, or annual review—leaving critical factors like grid capacity, climate exposure, and equipment condition unmonitored for months. This gap means financial and operational risk can materialize and compound undetected, leading to stranded assets, unplanned failures, and mispriced insurance or investment decisions.
Solution
Sono provides a live, agent-read risk scoring platform that continuously evaluates every asset in a data center portfolio across five categories: revenue, capex cycles, opex, compliance, and insurance. The platform ingests data from existing historians, contract documents, and external sources like grid substations and climate models, then projects financial impact in euros today. It flags anomalies before they trigger alarms, traces root causes to specific equipment, and delivers ranked recommendations with confidence scores. For site selection, Sono combines grid access, water stress, and permitting queues into a single calibrated score, enabling comparison of candidates on a common basis. The system requires no new hardware or integration projects, as it is historian-native and physics-constrained to avoid suggesting impossible setpoints.
Target Audience
Primary customers are data center investors, operators, insurers, and sustainability teams who need continuous risk visibility to avoid stranded assets, optimize opex, and price risk accurately.
Features
- Live risk scoring across five categories: revenue, capex cycles, opex, compliance, and insurance, with each asset updated as inputs move
- Predictive maintenance and anomaly detection that reads existing historian data, identifies failure modes before alarms fire, and traces root cause to specific equipment
- Site selection scoring that combines grid capacity, water basin stress, and permitting queues into a single calibrated score against a reference population of European sites
- Financial impact projection in euros today, with the year a threshold is crossed for action
- Physics-constrained recommendations with confidence scores, ensuring no physically impossible setpoint is ever suggested
- No instrumentation required; works with existing historians and external data layers like power plants, substations, and climate zones