Front Office Solutions

Your pricing models, 100x faster

Your code, your models, compiled.

MatLogica does not replace your models. It makes them run 100 to 1000x faster, with the Greeks computed in the same pass. Your code and your IP stay yours.

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What MatLogica Does

We do not sell pricing models or analytics.

We make your existing code faster and help you build new models quicker.

Your Python/C++ pricing code → AADC → 100-1000x faster + auto Greeks

Before and after

Same codebase, same models, a different run time.

✗ Your Code Today

Exotic pricing 2-5 seconds
Greeks Bump & revalue
Cloud bill $$$
Optimisation Manual, ongoing

✓ Your Code With AADC

Exotic pricing 20-50ms
Greeks Automatic AAD
Cloud bill $
Optimisation Automatic

Same pricing models. Same methodology. Transformed performance.

Where front-office teams use it

None of these is a product we sell. They are what your own code does once it runs compiled.

RFQ Pricing

Price a complex structure in milliseconds, before the other dealers have answered.

Typical: 50-100ms for exotic with full Greeks

Real-Time Greeks

Delta, gamma, vega and cross-gamma from one adjoint pass.

Adjoint factor <1 means Greeks faster than price

Live Risk

P&L and risk that update as the market moves. A full portfolio in under 100 ms.

20 sessions per CPU core

Model Calibration

Calibrate vol surfaces and rate models as the market moves. Gradients through the solver come from AIFT, with no refactoring.

10-50x faster calibration

What-If Analysis

Scenarios replay through the same recorded kernel; nothing is recomputed from scratch.

Thousands of scenarios per second

Where did this number come from?

Set AADC_TRACE=1 and the run records every step with the line that produced it. A wrong price traces back to its source; a code change shows exactly what.

AADC Tracer, C++ and Python

Custom Payoff Acceleration

Autocallables, barriers, TARNs, Americans: the same recording, the same sensitivities.

Full AAD for any payoff structure

The compiler is ours; the models and the IP are yours.

Choose Your Implementation Path

Select the approach that best fits your front office needs

Legacy Optimisation

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 Optimisation

Reduce cloud costs by 50-99% with optimised compute

Proof Points

Client-Results

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

A Tier-2 European bank fixed the performance of its front-office risk infrastructure with 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 modelling codebase while unlocking new revenue streams.

Read Full Case Study
POC in 2-4 weeks. Production in 3-6 months. No rewrite required.
"One notable feature of AADC is that complex model calibration procedures do not require any special attention as is often the case with other AAD approaches. For example, we 'AADC-record' simple Dupire volatility calculations, regression based continuation value calibration and even Monte-Carlo based Cheyette model calibrations, with no special care needed to back-propagate adjoints."

Quant Development Lead

Tier-2 European Investment Bank

What we do, and do not do

✗ We Don't Provide

  • Pricing models
  • Market data feeds
  • Trading systems
  • Pre-built analytics
  • Risk management platforms

You keep your IP and models.

✓ We Do Provide

  • Compiler that accelerates your existing models
  • Automatic AAD for Greeks
  • Integration tools & support
  • Reference implementations
  • Performance optimisation

You get 100-1000x speedup.

Performance Evidence

Independent benchmarks demonstrating real-time margin capabilities

AADC vs GPU: 47× Faster SIMM with Exact Gradients

AADC C++ computes ISDA SIMM sensitivities at 34,000 evaluations/sec on CPU, 47× faster than GPU pathwise differentiation on NVIDIA H100. GPU brute-force fails to converge at scale due to noisy finite-difference gradients.

  • 34,000 SIMM evaluations/sec with AADC C++ on CPU
  • 47× faster than GPU Pathwise on NVIDIA H100
  • GPU brute-force fails to converge at 500+ trades
View Benchmark

SIMM Optimisation: 33K Evals/sec, 25× Faster than GPU

AADC C++ computes SIMM trade allocation gradients at 33,580 evals/sec, 25× faster than GPU. Optimises a 50K trade portfolio in 19 ms with 1-2 iterations to converge.

  • 33,580 evaluations/second with AADC C++
  • 25× faster than GPU implementations
  • 19 ms to optimise 50K trade portfolio
View Benchmark

See it on your own pricer

We run the benchmark on one of your models and show you the numbers.

Schedule Technical Call Try Interactive Demo
Or explore:
How AADC Works
Live Risk Architecture
Benchmark Details
SIMM Margin Optimisation

Frequently Asked Questions

Does MatLogica provide pricing models? +
No. MatLogica provides AADC, a compiler that makes your existing Python or C++ pricing code run 100 to 1000x faster with the Greeks computed in the same pass. The models and the IP stay yours.
How much faster can AADC make my pricing code? +
Typical speedups range from 100x to 1000x depending on the complexity. Exotic pricing that takes 2-5 seconds can run in 20-50ms. Monte Carlo simulations see the largest gains. Greeks computation via AAD achieves adjoint factor <1, meaning all Greeks are computed faster than the original price calculation alone.
How long does AADC integration take? +
A proof of concept takes 2 to 4 weeks; production deployment 3 to 6 months. Less than 1% of the code changes and nothing is rewritten: a type is swapped in the hot section and the compiler does the rest.