AI/ML Consulting
Applied AI/ML systems, from prototype to production.
I help teams get past the demo — to systems that hold up under real users, real data, and real cost constraints.
Scoping
Deciding where machine learning actually earns its keep versus where simpler logic wins — before a single model is trained.
Building
Prototypes, evaluation harnesses, and the unglamorous plumbing — data pipelines, retrieval, guardrails — that decides whether an AI feature survives contact with production.
Operating
Deployment, monitoring, and keeping latency and inference cost honest once real traffic arrives.
This is the same work behind Siberiasoft’s own products, both built AI-first rather than bolted on:
FAQ
How do I know if my problem actually needs machine learning?
Often it doesn’t — and saying so is part of the job. The first step is deciding where ML earns its keep versus where simpler logic is cheaper, more reliable, and easier to maintain. A model gets trained only when it clearly beats the alternative.
Do you work with teams that have nothing in production yet?
Yes — that first crossing is most of the work: from a promising demo to something that survives real users, real data, and real cost. The evaluation harnesses, data pipelines, retrieval, and guardrails usually matter more than the model choice.
Can you take a prototype all the way to production?
Yes — scoping, building, and operating: deployment, monitoring, and keeping latency and inference cost honest once real traffic arrives.
Have a project in mind?
admin@siberiasoft.com