Most companies don't need machine learning.
They need reliable data infrastructure
We build the systems that make your data usable: pipelines that work, dashboards that inform, and ML that actually ships to production.
Five core capabilities
From fragmented data to operational intelligence
Data Infrastructure & Engineering
Connect scattered data sources (ERP, CRM, databases, APIs) into unified systems. Automated ETL pipelines that eliminate manual reporting and create a single source of truth.
Analytics & Business Intelligence
Turn data into operational visibility. Power BI dashboards, KPI monitoring, executive reporting. Answer the questions: Are we profitable? Where are the bottlenecks?
Predictive Analytics & Machine Learning
Deploy models that predict business outcomes: demand forecasting, churn prediction, formulation optimization, recommendation engines. Full production pipelines with monitoring and retraining.
Data Applications & Internal Tools
Custom platforms that combine analytics, ML, and interfaces. SaaS products, decision support systems, operational monitoring — built for your team's workflow and delivered to production.
Data Strategy Consulting
2–3 week engagements: assess data maturity, design architecture, identify ML opportunities, deliver implementation roadmap. Clear priorities, not generic frameworks. Often converts to full projects.
Client results
Aluminum manufacturers had no way to simulate alloy formulations before physical testing, resulting in material waste and slow R&D cycles. We built Metallyx — a multi-tenant SaaS platform where engineering teams across multiple facilities manage alloy inventories, run casting job workflows, and get instant ML-powered predictions on formulation properties before any metal is poured.
Business impact: 15% material waste reduction, R&D cycle time cut in half
A leading reinsurance firm processed millions of records manually across three actuarial data models with no unified pipeline. We built a modular reporting platform with automated validation, a metadata warehouse, role-based access control, and Power BI dashboards — eliminating the manual reporting cycle entirely.
Business impact: 5M+ records processed, 200+ hours saved monthly, 5-day cycle reduced to same-day delivery
A Harvard-affiliated research platform needed to automate the extraction of scientific replicates from academic literature — a process that was entirely manual and bottlenecked researcher output. We built an AI-powered tool that categorizes papers, extracts methodology data, and routes structured results at scale.
Business impact: 85% reduction in manual research tasks, deployed to 40+ brokerage companies
Infrastructure before algorithms
Most companies think they need machine learning. In reality, they first need reliable data pipelines.
We're a tech company that builds data science, ML, and software solutions — from SaaS platforms and custom applications to data pipelines and analytics infrastructure. We understand the full stack: infrastructure, analytics, and the ML that creates real competitive advantage when the foundation is solid.
Tech Stack
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Have a data problem? Tell us what you need. We respond within 24 hours.