Methodic is an applied AI lab building AI operators for the specialized workflows of services businesses. Refinery, our in-house platform, learns how your business works, finds valuable automation opportunities, and builds, tests, and deploys operators in your existing systems.
Start with a defined workflow. Expand toward entire departments as performance supports it.
BUILT FOR MID-MARKET SERVICES BUSINESSES
Some of your most valuable work is unique to your business. It depends on years of expertise, company-specific rules, and decisions that span disconnected systems. Standard software rarely fits.
THE SOFTWARE GAP
A workflow can be worth millions to your business even if only a handful of companies do it the same way. Traditional software needs a large market to justify the build. That leaves valuable, specialized work in people's hands.
THE RESOURCE GAP
Mid-market services firms have enterprise-level complexity without enterprise-level engineering teams. Custom development and large consulting engagements can cost more than the workflow can justify. The work stays manual.
AI Operator in Production
In the operator’s first 1.5 months.
Identified revenue, not a measure of cash collected.
FROM QUESTIONS TO BUSINESS OUTCOMES
Answer a question
You guide each exchange.
Carry out an assignment
You define the work to be done.
Own a business outcome
You set the objective, boundaries, and review points.
RESEARCH IN PRACTICE
We reconstruct what an expert knew, which action they took, and why. Those cases give operators a grounded way to learn company rules and exceptions.
We evaluate operator decisions against real cases and agreed goals. Failures show where the system needs better context, stronger rules, or human review.
Live results and reviewer feedback inform proposed changes. We test those changes before deployment and expand autonomy as the evidence supports it.
INSIDE REFINERY
Refinery supports the full process of building an operator, with your team’s expertise and review at the steps that matter.
Connect the software, data, and tools your team uses to see how work moves through the business.
Identify bottlenecks, rank automation opportunities by economic impact, and define the scope.
Use system records and interviews to capture rules, exceptions, inputs, and expected outputs.
Build an operator that carries out the workflow and produces outputs your team can review.
Review decisions, correct failures, and test again until the work meets the agreed goals.
Connect the operator to business systems. Monitor results and test improvements before release.
Our ambition is an autonomous workforce that can run entire departments and businesses. We start with one workflow, prove it in practice, and expand what operators can take on.
Tell us where work gets stuck, which systems it touches, and what a better result would be. Our team will get back to you within one business day.
We'll be in touch within one business day.