is your AI workhorse
Unlock your existing compute power for AI
Add AI to your enterprise applications safely, while making them faster and token costs immaterial
Fractal lets your organization put AI to work on its core business systems without risking those systems, its data or its budget. Fractal provides a controlled path to AI applications that cost half as much and are ten times faster.
The decision
Every enterprise is under pressure to add AI to the applications that run the business. The usual approach connects an AI model directly to production systems and data. That approach is risky, because an AI model that makes a mistake can damage the records the business depends on. It is expensive, because AI providers charge for every piece of data the model reads. It also exposes sensitive data to the model.
Fractal takes a different approach. It builds a digital twin: a live, continuously updated copy of your existing systems, running on inexpensive hardware you control. AI works only on the twin, so your production systems cannot be harmed. The AI model only translates requests into instructions and turns results into plain-language summaries, so it never sees your private data and your AI costs stay small.
Starting with that first, low-risk step, Fractal can go on to provide a hot backup of your existing applications and, when you are ready, replace them with faster, lower-cost Fractal versions. The first step is a 90-day deployment at production scale that runs alongside your existing systems.
Performance and cost figures are minimums. Fractal-reported results from Fortune 500 production deployments in utilities, telecommunications and financial services are far larger (see the benchmarks).
The hidden risk: AI with access to your systems of record
Enterprise AI applications such as billing automation, customer care and transaction processing need read/write access to 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, conflicts between concurrent agents and unexpected edge cases can all corrupt, overwrite or destroy 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.
More How AI corrupts structured data → Why guardrails and sandboxes aren't enough →
What a Fractal deployment gives you
Each benefit below links to the part of How it works that explains it.
AI without risk to your systems
AI works on the Fractal digital twin, never on the systems of record. Data flows only one way, into the twin. Nothing the AI does can corrupt your production data or applications.
How the digital twin works →AI you can rely on
The AI model writes a small program; Fractal runs it. The same question gives the same answer every time, and every number can be traced and audited, like any other enterprise software.
Deterministic AI →Your data stays yours
Private and sensitive data is never passed to an AI model. The model sees only the request and the summarized results. The data stays on hardware you control, which guarantees data sovereignty.
AI at the edges →AI token costs become immaterial
With the model at the center of the work, AI costs grow with every record it reads. With Fractal, cost depends only on how complex the question is, not on how much data is behind it. A large expense becomes a negligible one.
Token economics →Hot backup at a tenth of the cost
The twin is a live copy of your applications and data, so it can serve as a hot backup and failover system. It costs about one-tenth as much as the systems it protects.
Live digital twin →Runs where you need it
Fractal runs on-premise, in the cloud, or on devices distributed around the world, wherever you interact with customers, partners and the outside world. The same application runs unchanged on all of them.
One stack, any platform →What changes when you add Fractal
Same workloads, same data. This is what changes when AI runs on a Fractal digital twin instead of directly on your systems of record.
| Dimension | 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 |
| Billing cycle runtime | 90+ hours | 9 minutes |
| Infrastructure cost | Data center: $ millions | 10 small computers: about $20,000 in total |
| Software licensing | Database, virtualization and others | Eliminated |
| AI token cost | Grows with every record the model reads | Flat: depends only on how complex the question is |
| New feature delivery | 1–6 months | Daily |
Measured across Fortune 500 production deployments in utilities, telecommunications and financial services.
A safe, controlled path to enterprise AI
You don't have to bet the business on a cutover. Each stage delivers value on its own, and your existing applications keep running until you decide to retire them.
- Stage 1 · within 90 days
Add AI on a digital twin
Fractal builds a twin of your existing systems and adds AI capabilities to it. The twin runs in parallel with production and is measured against it every day.
Result: safe AI capabilities, at production scale - Stage 2
Use the twin as a hot backup
Because the twin stays in sync with production, it can take over if an existing system fails. It provides resilience you would otherwise have to buy separately.
Result: failover at 1/10 the cost - Stage 3 · on your timeline
Replace with the Fractal version
Once the Fractal version has proven itself against live data, move workloads to it and retire the original. There is no hard cutover date.
Result: ≥ 50% lower cost, ≥ 10× faster
Why it is low risk: at every stage the existing applications remain in place and unchanged. Decisions to move forward are based on results measured against your own production data, not on projections.
Technical detail The 90-day parallel proof of concept → How the digital twin stays in sync → Where the cost and speed gains come from →
Safe AI, real performance, at enterprise scale
Production results from Fortune 500 deployments running Fractal digital twins. Each links to that industry's solution library.
10M customers billed on $20K of hardware
Over 1,000× faster, with zero risk to the systems of record.
TelecommunicationsApplication runs over 1,000× faster
90% less storage and zero downtime.
Water utilitiesRate validation across millions of customers
$500K in consulting saved.
Gas utilitiesReal-time rate simulation
Across the entire customer base, in minutes rather than months.
Financial services360-degree customer insight
From every data source, in real time, with a full audit trail.
Recommended next step
Approve a 90-day Fractal deployment for one business application. Fractal will build the digital twin on commodity hardware, add AI capabilities, and run it at production scale alongside the existing system. At day 90 you will have measured performance, accuracy and cost data from your own operations, and a clear basis for deciding how far to go.
How it works describes the 90-day plan in detail.
See what safe, low-cost AI looks like on your data
A 90-day deployment at production scale, alongside your existing systems. No disruption. Your data. Real numbers.