AI-Native Engineering
We've been building intelligent systems for 25 years — rule engines, recommendation platforms, pattern recognition, machine learning, operations research. When modern AI tools arrived, we didn't start from scratch. We had 25 years of production engineering to accelerate. Claude Code, TensorFlow, local LLMs — they're the latest tools in a workflow that's always been about making software smarter.
AI as a Development Accelerator
AI-Assisted Development
Every engineer codes with Claude Code daily. Architecture, implementation, testing, and documentation — AI is embedded in the entire development lifecycle, not bolted on at the end.
Accelerated Delivery
AI-augmented development compresses timelines without cutting corners. We shipped a full platform from Figma wireframes to production in three months.
Production ML Engineering
TensorFlow, local LLMs, vector databases, real-time inference, operations research. We build and deploy ML and optimization systems that run in production — not slide decks about what's possible.
AI Baked Into Every Product
Every product in our portfolio has AI at its core — not as a feature flag, but as the reason it works.
Master Data Watchdog
AI recommender that detects anomalies and suggests corrections before inconsistencies cascade across systems
VODACIS
On-premise AI stack — real-time transcription, voice agent, local LLMs — all running on your hardware with full data sovereignty
Bottle Bill Manager
Local LLM validates product data semantically — catching misclassifications, incorrect attributes, and implausible categories
PACE
Pattern-discovery engine that learns categorization rules from transaction data instead of requiring manual rule authoring
HBRMS
Built with AI-assisted development from Figma wireframes to production in three months — proving the methodology at speed
Engineers Who Ship AI
Our team includes engineers with 30+ years building production AI/ML and operations research systems — from a $465M DOD recommendation engine at Cisco to load planning optimization for Levi Strauss to real-time transcription running on local GPUs. When we say AI-native, we mean our people have been building intelligent systems since before it was a marketing buzzword.
Meet the Team →AI Engagements May Qualify for R&D Tax Credits
Under Section 41, AI and machine learning development work — training models, building intelligent features, developing novel algorithms — can qualify for federal R&D tax credits of 6–10% of qualified expenses, plus applicable state credits. Ask your tax advisor how Axiomize engagements could reduce your effective cost of innovation.