From model fine-tuning to full-scale manufacturing, I help teams build, deploy, and scale AI and engineering solutions end to end.
Fine-Tuning Models
Custom fine-tuning of large language and machine learning models on your data — improving accuracy, reducing inference costs, and aligning outputs with your specific domain.
Data Engineering
End-to-end data pipelines, ETL/ELT, and data infrastructure design so your data is clean, reliable, and ready to power analytics and AI systems.
R&D Software and Hardware
Research and development for novel software and hardware solutions — from early prototyping and proof-of-concept through to production-ready systems.
Small Scale Manufacturing
Design, prototyping, and small-batch production support for hardware products — bridging the gap between concept and manufactured reality.
AI Business Integration
Seamless integration of AI capabilities into your existing workflows, tools, and systems to drive efficiency and unlock new value.
ML DevOps
Robust MLOps pipelines for training, deployment, monitoring, and scaling machine learning models reliably in production.
Not sure which service fits your project? Get in touch and let’s figure it out together.
Frequently Asked Questions
How does pricing work for AI and machine learning projects?
Every project is scoped individually based on complexity, data readiness, and timeline. Reach out through the contact page with a short project description and I’ll follow up with a free, no-obligation quote.
Do you work with startups and small teams, or only larger companies?
Both. I’ve worked with early-stage startups validating an AI feature as well as established teams scaling out data infrastructure and ML DevOps pipelines. Engagements are sized to fit the project.
What does the model fine-tuning process typically involve?
It starts with understanding your data and target outcomes, followed by data preparation, fine-tuning, evaluation against your use case, and deployment — with the goal of a model that performs reliably on your specific domain, not just generic benchmarks.
Can you integrate AI into a product or workflow we already have, rather than building from scratch?
Yes — AI Business Integration is one of the core services. Existing tools, codebases, and workflows are usually the starting point; the goal is adding AI capability without disrupting what already works.
How long does a typical project take?
It depends on scope. A focused fine-tuning or integration project can often be completed in a few weeks, while larger data engineering or MLOps builds may run longer. A realistic estimate comes after an initial scoping conversation — get in touch to start one.