Accelerate Development, Reduce Costs, Modernize Legacy Systems

Your models. Your IP. Dramatically faster.

AADC empowers quant technology teams to build faster, spend less on infrastructure, and breathe new life into legacy code. Python-based platforms with C++ performance, or accelerated C++ with minimal changes.

Schedule Technical Call See Challenges We Solve

What MatLogica Does

We don't replace quants or provide models.
We empower quants to build and run models 6-1000x faster - with automatic Greeks.

Your Python/C++ models AADC Compiler 6-1000x faster + auto AAD

The Transformation

Same models. Same methodology. Your IP protected. Transformed performance.

✗ Quant Development Today

⏱️
Model development Months of optimization work
🐍
Python "Too slow for production"
📊
Greeks Manual AAD or bump & revalue
🏗️
Greenfield builds Always postponed - "too expensive"
💰
Cloud/compute costs Spiraling upward

✓ Quant Development With AADC

⚡
Model development 3-4x faster to production
🐍
Python Faster than hand-optimized C++
📊
Greeks Automatic - adjoint factor <1
🏗️
Greenfield builds Production in <1 year
💰
Cloud/compute costs 50-99% reduction

You keep your models, your IP, your competitive edge. We just make everything faster.

Sound Familiar?

Common challenges we help quant teams solve

Management wants vendor solutions, but you want to keep IP in-house?

Build in-house with AADC. Get vendor-class performance while retaining full control of your models and methodology.

→ 200x faster XVA, $0 vendor costs

Models too slow and complex for production?

AADC accelerates your existing code 6-1000x with minimal changes. No rewrite required.

→ <1% code changes

Greenfield build always postponed?

Python-first development with AADC means production-ready platforms in months, not years.

→ Production in <1 year

Python too slow, but C++ legacy is a barrier?

AADC Python outperforms hand-optimized C++. Use Python for new development, accelerate C++ legacy.

→ 277x faster Python

Choose Your Implementation Path

Select the approach that best fits your quant technology needs

Legacy Optimization

Accelerate existing C++ and Python codebases without rewrites

Greenfield Development

Build new applications with performance and AAD built-in

Open-Source Acceleration

Supercharge QuantLib, ORE, and other open-source libraries

Cloud Optimization

Reduce cloud costs by 50-99% with optimized compute

"MatLogica's product changes the paradigm for quantitative software development eliminating the need to invest in optimizations. Quants can now focus on the models, and performance will be taken care of by MatLogica's JIT compiler."

Paul A. Bilokon

CEO, Thalesians Ltd & Visiting Professor, Imperial College London

Let's Be Clear

✗ We Don't Replace

  • Quants or quant teams
  • Your pricing models
  • Your risk methodology
  • Your proprietary IP
  • Your development process

Your team, your models, your edge.

✓ We Empower

  • Quants to build models 3-4x faster
  • Models to run 6-1000x faster
  • Python to match C++ performance
  • Teams to use automatic Greeks
  • Organizations to cut cloud costs 50-99%

More output, less infrastructure.

Solutions by Role

Accelerate Python Models 345× with AADC

Prototype in Python, achieve C++ performance. Use AADC to accelerate your existing Python pricing models with minimal code changes — no rewrites required.

Learn More

Make Your Pricing Models 100x Faster

MatLogica doesn't replace quant models — we make them run 100-1000x faster with automatic Greeks. Keep your IP, your code, your competitive edge.

Learn More

AADC Solutions for Risk Management

AADC accelerates your risk models 6-1000x with automatic, stable sensitivities. Meet regulatory deadlines, improve P&L attribution, and make Monte Carlo affordable—using the models you already trust.

Learn More

Ready to Accelerate Your Technology Stack?

Learn how AADC works, or schedule a technical deep-dive with our engineering team

How It Works Schedule Technical Call

Or explore: How AADC Works | Full Benchmark Details | Case Studies

Frequently Asked Questions

Can Python really be fast enough for production quant systems with AADC?
Yes, AADC can accelerate Python code up to 1000x, achieving performance that exceeds hand-optimized C++. This enables building complete Live Risk platforms in Python that go to production in less than 1 year. AADC integrates with NumPy and provides automatic AAD for Python workflows.
How much can AADC reduce cloud infrastructure costs?
AADC typically reduces cloud costs by 50-99% through 6-1000x efficiency improvements. The same workloads require dramatically fewer compute instances and shorter runtimes. Additionally, AADC's hybrid architecture allows you to keep models on-premises while deploying only encrypted binary kernels to the cloud.
Can AADC modernize legacy C++ code without a full rewrite?
Yes, AADC accelerates existing C++ code 6-100x with typically less than 1% code changes. This preserves the institutional knowledge embedded in your codebase while delivering modern performance. You can modernize incrementally without risky big-bang rewrite projects.
How does AADC accelerate QuantLib and ORE?
AADC has demonstrated 245x acceleration of ORE (Open Source Risk Engine). It provides vendor-class performance while maintaining the flexibility and control of open-source. AADC automatically adds AAD capabilities to QuantLib models, enabling complete Greeks computation.
What programming languages and platforms does AADC support?
AADC supports C++ (11/14/17/20) and Python (with NumPy/SciPy integration). It works with standard compilers (GCC, Clang, MSVC) without special toolchains. AADC runs on Linux and Windows, and can be deployed on any cloud provider (AWS, Azure, GCP) or on-premises.
What is the typical ROI timeline for AADC adoption?
Most organizations see ROI within 6-12 months through a combination of infrastructure cost savings (50-99% reduction), reduced development time (5x faster delivery), and avoided rewrite costs. The exact timeline depends on your starting point and implementation path.