What we offer

Software, models, pipelines, and a team that can use them.

Four service lines. Most engagements combine at least two — usually a build, paired with training for the people who'll run it day to day.

Enterprise software illustration

Enterprise Software

Backends, internal tools and data platforms built around how your team actually works. We design for maintainability from day one — clean handoff, real documentation, no dependency on us to keep it running.

Model training and fine-tuning illustration

Model Training & Fine-tuning

Fine-tuning, evaluation harnesses, and deployment for models that need to perform on your data — not a public benchmark. Includes reinforcement learning and multi-agent systems where they're the right fit.

Data pipelines and agentic automation illustration

Data Pipelines & Agentic Automation

Multi-agent systems and validation pipelines that process data reliably at scale — the infrastructure layer that makes everything else in a company's AI stack actually work.

AI staff training illustration

AI Staff Training

Practical, role-specific sessions that get a non-technical team comfortable using AI tools in their actual daily work — not a generic slide deck. This is how we've worked with every one of our auto-service partners.

Under the hood

Our stack

The tools we reach for most — picked for the problem, not the resume line.

Python
PyTorch
Ray / RLlib
TensorFlow
FastAPI
Docker
Kubernetes
PostgreSQL
React
TypeScript
Terraform
GitHub Actions
Anthropic API
Jupyter
Python
PyTorch
Ray / RLlib
TensorFlow
FastAPI
Docker
Kubernetes
PostgreSQL
React
TypeScript
Terraform
GitHub Actions
Anthropic API
Jupyter
Python
PyTorch
Ray / RLlib
TensorFlow
FastAPI
Docker
Kubernetes
PostgreSQL
React
TypeScript
Terraform
GitHub Actions
Anthropic API
Jupyter
AI Staff Training, in detail

How the training program runs

Built for teams with no ML background — the goal is confident daily use, not certificates.

1

Audit the workflow

We spend time with the team before writing a single slide — what tools they already use, where the friction actually is, what "using AI" would even mean for their job.

2

Build role-specific sessions

Front-desk staff, technicians and managers get different sessions, because they need different things from the same tools.

3

Train hands-on, on real work

No sandbox exercises — sessions run on the team's actual tickets, quotes, and customer messages.

4

Follow up after go-live

We check back in after the team has been using the tools on their own, to fix whatever the first sessions didn't cover.

Not sure which service line fits your problem?

Tell us what you're working with — we'll tell you honestly whether AI is the right tool for it.

Get in touch