Cloud Optimization

Slash Cloud Costs by 50-99%

AADC's 6-1000x efficiency improvement transforms cloud economics. Same workloads, dramatically lower costs. ROI in 2-4 months.

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Transform Your Cloud Economics

Cloud computing costs can spiral out of control for compute-intensive quant workloads. AADC's efficiency improvements let you run the same calculations on a fraction of the infrastructure—turning your cloud bill from a liability into a competitive advantage.

Cloud Cost Pain Points

Sound familiar? These cloud challenges strain budgets

Cloud bills growing faster than revenue?
Monte Carlo consuming too many resources?
Scaling costs getting out of control?
Hard to justify cloud spend to CFO?
Wasted compute during off-peak hours?
Performance bottlenecks limiting throughput?
Over-provisioning to meet deadlines?
Vendor lock-in inflating instance costs?

The AADC Solution

Slash cloud infrastructure costs by 50-99% while maintaining or improving performance. AADC's 6-1000x efficiency improvement transforms cloud economics—run Monte Carlo, XVA, and risk jobs on a fraction of current resources. Zero infrastructure changes required—deploy the same binaries across on-prem, cloud, or hybrid.

50-99% Cost Reduction
Immediate infrastructure savings
6-1000x Efficiency
Same results, fraction of compute
Source Code Stays On-Premises
Only binary kernels deployed to cloud
Any Cloud Provider
AWS, Azure, GCP, or hybrid

Perfect For:

Organizations with high cloud compute costs (>$500K/year)Teams running Monte Carlo simulations in cloudCTOs and CFOs under pressure to optimize cloud spendingApplications with elastic scaling needsHybrid cloud deployments

Key Benefits

50-99% Cost Reduction

Dramatic infrastructure savings

6-1000x Efficiency

Same results, fraction of the compute

Source Code Stays On-Premises

Only binary kernels deployed, not source code

2-4 Month ROI

Fast payback on investment

Proven Results

Client-Results

Tier-2 European Bank Achieves 15-20x Faster Risk with 70% Less Code

A Tier-2 European bank transformed their struggling front-office risk infrastructure using MatLogica AADC. They achieved 15-20x speedups compared to manual adjoint differentiation, reduced overnight batch from 8+ hours to 2 hours, and eliminated 70% of their modeling codebase while unlocking new revenue streams.

  • ›15-20x faster risk vs manual adjoints
  • ›Overnight batch: 8+ hours to 2 hours
  • ›70% codebase reduction
  • ›50% grid cost savings
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Legacy Optimization

Integrate AADC to modernize existing analytical systems with minimal code changes. Preserve institutional knowledge embedded in your codebase while achieving 6-100x speedup and automatic AAD.

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Greenfield Development

Use AADC to develop C++/Python models faster, without optimization concerns. Get production-grade performance and automatic AAD from day one. Focus on models, not infrastructure.

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Open-Source Acceleration

Integrate AADC with open-source frameworks like QuantLib and ORE to get community validation plus proprietary-grade performance. No vendor licensing fees, automatic AAD for all models.

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Ready to Cut Your Cloud Costs?

Calculate your potential savings and see how AADC can transform your cloud economics.

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Frequently Asked Questions

How quickly will we see cost savings?
Infrastructure savings begin immediately upon deployment. Most organizations see positive ROI within 2-4 months, with savings of $500K or more for every $1M in prior cloud spend.
How does AADC keep source code secure in the cloud?
AADC's hybrid architecture keeps source code on-premises. Only binary kernels are deployed to the cloud - source code is not included in kernels.
Which cloud providers does AADC support?
AADC works with all major cloud providers (AWS, Azure, GCP) as well as private cloud and on-premises deployments. The kernel architecture is platform-agnostic, giving you deployment flexibility.
How does AADC compare to using spot instances?
Spot instances typically save 20-40% but come with interruption risk and capacity constraints. AADC delivers 50-99% savings through efficiency gains that work alongside spot instances—you can combine both approaches for maximum savings.