Thealgorithmisyourcompetitivemoat.Weengineerit.
Proprietary algorithms for routing, optimization, pricing, fraud detection, and recommendation — built exclusively for your business logic and data.
What we deliver
Off-the-shelf software uses generic algorithms designed for the average use case. Your business is not average. Digital Prizm's Custom Algorithm Development practice builds proprietary computational engines that encode your specific business rules, constraints, and optimization objectives — creating a technical moat that competitors cannot replicate by buying the same SaaS tool.
We've built routing engines that reduced fleet costs by 28%, pricing algorithms that increased revenue by 19%, and fraud detection systems that cut false positives by 60% while catching 40% more fraud. Every algorithm we build is mathematically rigorous, computationally efficient, and designed for production-scale throughput.
Capability Depth
Core Capabilities
Route & Dispatch Optimization
Vehicle routing problem (VRP) solvers with time windows, capacity constraints, and multi-depot support — reducing fleet costs by 20–35%.
Dynamic Pricing Engines
Real-time pricing algorithms that balance demand, supply, competitor pricing, and margin objectives — updated in milliseconds.
Fraud Detection Systems
Graph-based and ML-powered fraud detection that identifies anomalous patterns in real time with sub-100ms decision latency.
Recommendation Engines
Collaborative filtering, content-based, and hybrid recommendation systems that drive engagement and revenue across e-commerce and media platforms.
Scheduling & Resource Allocation
Optimal scheduling algorithms for workforce, equipment, and resource allocation under complex constraints and shifting priorities.
Demand Forecasting
Time-series forecasting models that predict demand at SKU, location, and time granularity — enabling proactive inventory and capacity planning.
Algorithm Performance vs. Baseline
Measured improvements across 50+ algorithm deployments. Route efficiency and revenue shown as index (100 = baseline); detection rates shown as percentage.
The Challenge
A digital payments platform was experiencing 8.2% false positive rate in fraud detection, causing customer friction and support costs, while still missing 38% of actual fraud cases.
Our Solution
Digital Prizm engineered a graph-based fraud detection algorithm combining transaction network analysis, behavioral biometrics, and real-time velocity checks — deployed as a sub-50ms decision API.
What you receive
Every engagement includes these deliverables as standard
Frequently Asked Questions
ML models learn patterns from data. Custom algorithms encode explicit business logic, constraints, and optimization objectives — often outperforming ML in domains where rules are well-defined and data is limited.
Ready to get started?
Schedule a consultation with our Custom Algorithms specialists. We'll assess your requirements and propose a tailored solution within 48 hours.
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