Magnus Artifex
Built for Systems
That Can't Afford
to Fail.
Magnus Artifex engineers mission-critical integrations, financial infrastructure, and AI-powered automation for companies operating at scale, where reliability isn't a feature, it's the requirement.
Contributed to systems at
Deep in the stack.
Closer to the data.
Magnus Artifex is a software engineering company with deep roots in fintech, retail operations, and logistics infrastructure. We design and build systems that integrate cleanly, scale reliably, and deliver measurable results, without the overhead of large agencies or the risk of generalist shops.
Our background spans supply chain operations through enterprise-grade computer science, giving us an unusual ability to reason across the full stack: from business logic and data pipelines to financial APIs and intelligent automation.
We don't build prototypes and leave. We work on production systems, alongside engineering teams, in environments where downtime has a real cost.
Where we've
done the work.
Six industries. Thousands of production deployments. Systems that process real money, real orders, and real decisions at scale.
Financial Integrations
We've contributed to production integrations with Equifax, TransUnion, Plaid, Stripe, Chase, and Dwolla, building risk pipelines, payment flows, identity verification, and banking API orchestration for real financial products.
Retail & Commerce Systems
We've worked on BOPIS workflows, POS integrations, inventory systems, and promotional engine development for major retail brands, including promo code systems for Ann Taylor and Loft outlets.
API Development & Automation
We design clean, well-documented APIs and webhook-driven architectures that connect disparate systems cleanly, from third-party data providers and banking services to internal tooling and operational workflows.
Risk & Detection Models
We've contributed to risk detection models for financial and identity systems, building logic that flags anomalies, enforces policy, and helps products make faster, defensible decisions at scale.
Mobile Engineering
We've contributed to React Native applications for Rue21 and Ann Taylor, delivering mobile commerce features, checkout improvements, and performance work within active, production-scale codebases.
AI & Intelligent Systems
We integrate practical AI into real production environments, LLM-powered prompt flows, automated classification, and intelligent decision support built on Ollama and ChatGPT infrastructure.
AI that works
inside the system.
We don't sell AI hype. We build AI into systems where it earns its place, automating decisions, surfacing insights, and reducing friction at the edges where human review can't scale.
LLM Integration, Not LLM Theater
We've integrated ChatGPT and Ollama into production workflows, not demos. From intelligent prompt engineering to context-aware automation, we build AI that earns its place in the system.
Risk Modeling with Real Stakes
We've contributed to risk and fraud detection models in live financial environments, systems where false negatives have dollar consequences. Our models are informed by real data, not textbook assumptions.
Automation That Scales Decisions
We build automation pipelines that reduce the surface area requiring human review, using classification, detection, and signal aggregation to surface what actually needs attention.
Prompt Engineering as Systems Work
We treat prompt engineering as engineering, versioned, tested, and integrated into existing pipelines. Context construction, output structuring, and model selection are all first-class concerns.
Luminary
AI-powered reporting for teams that need answers, not dashboards.
Upload your data, build reports, and generate insights instantly, no BI tools required.
Years of work.
Across every layer.
Our background didn't start in a browser. It started in warehouses and distribution centers, which gave us a fundamentally different understanding of what software has to do to matter.
Logistics & Supply Chain
Before writing a single line of professional code, we ran supply chain operations, managing inventory flows, coordinating fulfillment, and optimizing the physical systems that underpin modern commerce. That operational lens shapes how we build.
Operations → Engineering pipeline thinkingRetail Engineering
We've contributed to engineering work at Rue21, Ann Taylor, and Loft, working on mobile applications, promotional systems, BOPIS workflows, and POS integrations that serve millions of customers across active, high-traffic platforms.
Retail commerce at scaleFintech & Financial Systems
We've contributed to financial infrastructure involving Equifax, TransUnion, Plaid, Stripe, Chase, and Dwolla, building the identity verification flows, payment pipelines, and risk models that financial products depend on.
Identity · Payments · Risk"Our path from supply chain operations to computer science isn't a detour, it's the advantage. We understand how systems fail in the physical world, and we build software accordingly."
Magnus Artifex
Alonzo King
Founder & Lead Engineer
Alonzo King
Software Engineer · Integrations · AI
I'm a software engineer with more than nine years of experience building secure, scalable applications for real production environments. My recent work focuses on financial software, combining Python, machine learning, and real-world data from providers like Consumer Reports and Plaid to help teams make better decisions faster.
Before Magnus Artifex, my work moved through application security, fintech integrations, risk modeling, and operational systems. That mix shapes how I build: software should be fast and useful, but it also has to protect the integrity of the data and the business relying on it.
I like the hard middle ground where complex data, practical engineering, and business context meet. Whether the work is a leasing model, a delinquency prediction tool, or a financial data integration, the goal is the same: turn ambiguity into systems people can trust.
Core Domains
Financial Data
Plaid · Consumer Reports · Risk signals
Identity & Risk
Security · Prediction models · Integrity
Retail Engineering
BOPIS · POS · Inventory sync
Applied AI
Python · ML workflows · Automation
Cloud Infrastructure
AWS · API architecture · Webhooks
Decision Systems
Leasing · Delinquency · Risk tools
"I care about building software that holds up under pressure, systems that make complex data easier to trust, easier to act on, and safer to use."
Alonzo King
Let's build something
worth building.
Whether you're integrating financial APIs, scaling a retail platform, adding AI automation, or need a software engineer who understands the full stack, we'd like to hear about it.