Built for the world's most demanding data environments.

Electric utilities manage enormous volumes of structured data — meter reads, rate schedules, customer accounts, grid sensors — and must process it reliably at scale, often in real time. Traditional architectures buckle under this load. Fractal was built for it.

A major electric utility running Fractal through PicoTera can bill 10 million customers on $20,000 in commodity hardware, completing billing runs 100× faster than legacy systems. Rate simulation across the entire customer base takes minutes, not months of consultant time.

The digital twin architecture ensures that AI-assisted billing and analytics never touch your customer records directly — zero risk of corrupting the data that determines what customers owe.

Telecom companies operate some of the most complex billing environments in enterprise IT — millions of customers, dozens of service types, high-volume usage data, and regulatory obligations that demand accuracy. Errors in billing at telecom scale are both costly and visible.

PicoTera-implemented Fractal systems deliver billing runs 100× faster with 90% less storage than legacy platforms. The digital twin architecture allows AI-driven customer insight and billing analytics to run freely — without any risk of corrupting the underlying customer records.

Water utilities face the double challenge of aging infrastructure and increasing regulatory scrutiny. Billing accuracy, leak detection, and rate validation across large customer bases require analytical horsepower that traditional architectures can't efficiently deliver.

PicoTera has delivered Fractal implementations that run rate validation and billing analysis across millions of customer accounts, saving $500K+ in consulting costs on projects that previously required large teams of specialists.

Gas utilities manage billing complexity that rivals electric and water — varying rate structures, seasonal patterns, usage tiers, and regulatory requirements across large customer bases. They also face operational risk from undetected leaks and meter anomalies.

Fractal enables real-time rate simulation across the entire customer base — something that previously required months of batch processing or large consultant teams. Anomaly detection and leak signature analysis run continuously on the digital twin.

Financial services firms operate under the highest data integrity requirements in any industry. A corrupted transaction record isn't a nuisance — it's a regulatory event. AI-assisted analytics that write to source systems directly are a liability no financial institution can afford.

Fractal's digital twin architecture provides 360-degree customer insight from every data source — in real time, with a full audit trail — while ensuring AI never touches the underlying transaction records. Every write-back is explicit, authorized, and logged.

Insurance companies sit on massive structured datasets — policy records, claims histories, actuarial tables, customer profiles — that are rich targets for AI-driven analytics but dangerous to expose to AI write access. A corrupted policy record or claims database has immediate financial and legal consequences.

Fractal enables deep AI analytics across insurance data with full protection for source records. Fraud patterns, risk correlations, and financial forecasts are computed on the twin — with results promoted back to systems only through explicit, auditable processes.

Oil and gas operations generate enormous volumes of operational and sensor data — from wellhead telemetry to refinery process controls to logistics tracking. The challenge is not collecting data; it's processing it fast enough to be actionable.

Fractal's distributed architecture handles the wide-scan, aggregate workloads that operational analytics demands — at a fraction of the cost of traditional data platforms. Process anomaly detection, predictive maintenance, and supply chain analytics run in real time on the twin.

Logistics operations require data processing at the edge — point of delivery, warehouse, and distribution center — where latency matters and connectivity can be intermittent. Centralized architectures with cloud dependencies are poorly suited to this environment.

Fractal's agent-based architecture runs on commodity hardware at the edge — no cloud dependency required. Inventory analytics, delivery route optimization, and customer insight run locally, with synchronization back to central systems through the digital twin.

Retail operations generate high-frequency transaction data that must be processed daily for inventory management, financial reconciliation, and customer analytics. The nightly end-of-day processing window is often the critical bottleneck in retail IT systems.

Fractal dramatically compresses end-of-day processing windows — completing in minutes what previously took hours. Inventory analytics and customer insight run continuously on the digital twin, providing real-time operational visibility without touching the underlying transaction records.