moco

30-50% fewer FLOPS in inference -> lower latency, higher throughput, fewer missed SLAs.

Problem:
Fraud Detection models along the critical path must return responses within critical time windows (called SLAs) or be penalized. In moments of high throughput, transactions get queued and SLAs get missed.

For Citibank, a company with 10M transactions / day, assuming 0.1% missed SLAs, assuming $10 / missed SLA penalty that is $100k/day.

Solution:
moco offers a drop-in solution: a mathematical optimization library that takes in a trained model and a dataset and outputs a more efficient model, saving computations, latency, less queuing and thus fewer missed SLAs.

Key Benefits:

• Fewer Missed SLAs → Direct Dollar Savings
• Higher Throughput Without Buying More Infrastructure

• moco increases throughput on existing hardware, delaying or eliminating expensive infrastructure expansions.

• Faster, Lower-Risk Model Optimization

• moco slots into existing workflows and optimizes trained models in hours, not weeks.

Interested? Schedule a demo today!

Contact:

Sam Randall, Founder

LinkedIn, Email, Website