Fractal Computing
Enterprise AI that reads and writes to your databases carries a hidden, existential risk — data corruption. Fractal eliminates that risk with a digital twin architecture that also delivers 100× the performance with 90% less cost.
The Hidden Risk
Enterprise AI applications — billing automation, customer care, transaction processing — need read/write access to your databases and systems of record to do anything useful. That access is also the source of a critical, often overlooked risk.
AI systems are complex and non-deterministic. Prompt injection, model hallucinations, race conditions between concurrent agents, and unexpected edge cases can all result in corrupted, overwritten, or destroyed data. A single bad write to a billing database can mean wrong charges to millions of customers. The consequences can be immediate, widespread, and career-ending.
The Fractal Approach
Fractal creates a synchronized digital twin of your structured data — hyper-optimized for distributed processing and AI analytics. The twin stays continuously in sync with your source systems but lives in a separate, protected environment.
AI works on the twin. Your original data stays safe. Changes flow one way — from your systems of record into the twin — unless explicitly promoted back through a controlled, auditable process.
Fractal creates a live, continuously updated digital twin of your databases and systems of record. It is not a snapshot — it is a real-time replica that maintains full fidelity with your production data.
All AI processing — reads, writes, analytics, transformations — happens exclusively on the twin. Your systems of record are never touched by AI operations. Corruption risk goes to zero.
The twin is built from the ground up for distributed AI analytics using Locality Optimization — delivering 100× the performance with 90% less infrastructure cost than traditional database architectures.
By the Numbers
Same workloads, same data. Here is what changes when AI runs on a Fractal digital twin instead of directly on your systems of record.
Measured across Fortune 500 production deployments in utilities, telecom, and financial services.
| AI on Source Systems | Fractal Digital Twin | |
|---|---|---|
| Data corruption risk | Present — AI has direct write access | Zero — AI never touches source systems |
| Deployment timeline | 24 months | 90 days |
| Team required | 18 high-end consultants | 1 programmer |
| Bill cycle runtime | 90+ hours | 9 minutes |
| Infrastructure cost | Data center: $millions | 10 small computers: $10,000 total |
| Software licensing | Oracle, VMware, others | Eliminated |
| New feature delivery | 1–6 months | Daily |
Results
Production results from Fortune 500 deployments running Fractal digital twins.
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A 90-day parallel deployment runs alongside your existing systems. No disruption. Real numbers.