AI Features Built Into the Systems That Already Run Your Business
Most AI projects stall on the same question: can the system underneath actually feed the model? We start there. Before any build, we survey what your software stores, what it can emit, and where its seams are, then design the smallest insertion point that pays back. New capability runs in shadow mode alongside your existing process until its accuracy is measured against real outcomes, and only then does it touch anything that matters. Scope stays at the application layer: your team keeps infrastructure and DevOps.
Deliverables
Every engagement is scoped to deliver specific, measurable outcomes.
System Readiness Survey
A written review of what your software stores, what it can emit as events, and where its integration seams are. This decides what is feasible before anyone commits to a model.
Insertion-Point Design
Where AI enters an application decides its blast radius. We map candidate insertion points, from read-only suggestions to workflow automation, and sequence them by risk.
Data Pipelines
Event capture, cleaning, and retrieval built into your existing stack, because model output is only as good as the data your system can hand it.
LLM and Model Integration
Provider APIs wired in with guardrails, fallbacks, and token cost controls, with prompts kept in version control like any other code.
Shadow-Mode Rollout
New AI features run alongside the current process and get scored against real outcomes before they are allowed to write anything.
Evaluation and Monitoring
Accuracy tracked against ground truth in production, with drift alerts, so quality regressions surface before your users find them.
Technologies We Use
Production-proven tools selected for longevity, performance, and ecosystem health.
Why Teams Choose Rorix Technologies
The System Comes First
We build and maintain operational software: WMS, HRMS, and SaaS platforms. AI enters through the seams of a system we understand end to end, which is why our integrations hold up in production.
Honest Feasibility Calls
Some workflows need a model. Many need a rule. We tell you which one you are looking at before you spend, and we put the reasoning in writing.
Application Layer Only
Infrastructure and DevOps remain with your team. Our scope is the application: the features, the data flows, and the model integrations inside it.
Common Questions
Ready to Start Your AI Integration Project?
Tell us about your project and we will get back to you within one business day with a clear plan and an honest estimate.