A proven process, refined over 35+ machine learning projects 

Our machine learning team has brought dozens of successful projects to market. We’ll guide you through the process to help you minimize your risk and dodge the mistakes that push ML projects off course and over budget.


Your 4 steps to machine learning success


Duration: 1 day

Strategy Day

Pick the right problem

Your project begins with an intensive on-site Strategy Day.

It’s an exploratory, full-day session where we get to know your business in depth. We help you define the right problem to start with and choose the best approach based on your business, domain, goals, and data.

Preliminary validation of the solution helps to avoid costly missteps— like asking the wrong question, lacking sufficient data or choosing an overly complex problem.


Duration: 4 weeks

Proof of concept

Validate your solution

We leverage our engineering skill, experience, and pre-built compute infrastructure to arrive at PoC for your ML solution in 4 weeks or less.

Getting to PoC quickly and affordably is essential to get buy-in from your team early in the process. And to minimize the risk of a production solution that falls short of expectations.

At this stage, we validate the algorithm to be sure that it solves your problem. And then make adjustments or redirect our efforts based on what we’ve learned.


Duration: 2-6 months

Develop, integrate, test

Your ML solution goes live

Our team works in 2-week sprints to develop your solution, with bi-weekly calls to discuss our progress. Real-time communication via Slack or MS Teams keeps issues moving forward and helps bypass communication bottlenecks.

Then we take the solution live to evaluate its performance in your production workflow.

Finally, we automate everything, fine-tune the details, and hand over your solution— congratulations, your data is now officially working for you! 


Duration: Ongoing

Learn. Scale. Grow.

Build on your success

A successful ML application isn’t an endpoint— it’s a launching pad. So what’s next? 

We can help you quickly scale your solution to other locations, projects or products. Or build completely new strategies for helping to slay inefficiencies, improve processes or boost revenue.

Or your engineering team can take it from here and start building on what they’ve learned. We’re here to consult when your team gets stuck.

What to expect from us


Clear communication

Our engineers know how to specify projects and communicate results. You don't need to deal with ‘sales team.’


All-access, all the time

We work with a few clients at a time, so you have our full attention. The CEO & CTO manage your project personally and know every detail inside and out.


No counting hours

You never get a bill from us for hours worked. We agree to a project price and that’s what you pay. No cost overruns. No overtime.


Learn from our team

We work alongside your team and they get full access to our code throughout the project. So your team can learn from us to level up their ML skill set.

What you get

Proactive project management and a custom-built solution that works:

Project planning 

Expert interviews, data analysis, and academic research

Optimized algorithm

Feature engineering, algorithm selection, and tuning

Clean, tested & documented code

Keep it, use it and repurpose it as needed

Infrastructure and parallelization

From thousands to billions of decisions per day

Integration into your tool-chain

Auto-importing data, exporting results, or API accessibility. 

Complete transparency

Full access to plans, issues & our git repo

Project management

We keep the project on schedule and you in the loop

Frequent updates

Weekly engineering calls & bi-weekly milestone presentations

Real-time communication

Slack or Microsoft Teams to keep things moving