The math behind the decision
Data & Algorithms
Decisions driven by engines that score, match, forecast, and optimize on real data.
This is one of six engineering families at Martimus. On its own it solves a real, specific problem; combined with the others, it becomes part of one system rather than another tool to manage. Here is the problem it addresses, what we actually build, how the work is done, and where it shows up in real systems.
What business problem does this solve?
Important decisions are made on gut feel because the underlying data is trapped, unmodeled, or never turned into scoring, matching, or forecasting.
What does Martimus actually engineer?
We model the data and build the engine — scoring, matching, forecasting, optimization — and the pipelines that keep it fed and current.
How does it work?
We follow the same method every time — Discover, Model, Engineer, Validate, Deploy, Operate — so the result is a running system, not a prototype. See how we build →
What does it connect to?
We treat integration as a first-class concern: your existing CRM, accounting, databases, portals, and communications become part of one coherent system rather than another island. Integration engineering →
Proof
Real systems demonstrating data & algorithms.
Martimus-built internal system
Commercial Capital Platform
A full deal-to-funding platform: intake, underwriting workflow, a secure document room, and AI-assisted lender matching across a structured lender registry.
Martimus-built internal system
Hybrid Matching Engine
A hybrid engine: deterministic business rules narrow the field, a language model ranks and explains, and edge cases escalate for review.
Working technical demonstration
Large-Scale List Engine
A data engine that deduplicates and suppresses across a 56.8-million-row dataset, partitioned for throughput.
How is it deployed & operated?
Deployed where it belongs — public cloud, private infrastructure, self-hosted, or hybrid — and then operated: monitored, maintained, and improved, with rollback and recovery in place. Deployment & operations →
Where this shows up
- Unify Disconnected Systems — CRM, accounting, portals, databases, and email do not work as one system.
- Build a Proprietary Operating Platform — Off-the-shelf software cannot represent how your business actually works.
- Add an Intelligence Layer — You have data and systems but no decision support, retrieval, scoring, or forecasting.
FAQ
Data & Algorithms: questions we get asked.
What is a decision engine?
A system that turns data into a specific decision — scoring, matching, ranking, forecasting, or optimizing — rather than into a report someone still has to interpret. The logic is explicit, testable, and explainable.
How large a dataset can Martimus work with?
We have built and run deduplication and suppression across a 56.8-million-row dataset, partitioned for throughput. Scale is an engineering problem we plan for, not a limit we discover late.
Do we need clean data before this is worth doing?
No — cleaning is usually part of the work. Pipelines that deduplicate, normalize, and suppress are built alongside the engine that consumes them.