Newsroom
Podcasts, interviews, and features on putting AI agents to work inside mid-market operations, plus our own longer reads on the design decisions behind the work.
Press··The Manufacturers’ Network
Applied AI Labs Co-CEO Mike Fedorov joined Lisa Ryan to talk about what AI actually delivers on a plant floor, and how a mid-market manufacturer gets there without a seven-figure consulting programme.
Lisa’s audience is plant managers, operations leaders, and engineers — people close enough to the work to know exactly where it breaks. That proximity is where Mike started: what a $100M manufacturer can realistically get from AI without a $10M consulting bill, and why the answer turns far more on who you ask first than on which technology you pick.
The through-line: the projects that work do not start with the technology. They start with the people closest to the work, and with two questions worth asking before any tool is chosen.
What is the most acute pain you would love to have solved?
The problems people live with daily are the ones where a fix is felt immediately, and where the value is easiest to confirm against a baseline.
What is the improvement you have wanted for years?
Not every opportunity arrives as a pain. Some are ideas people have carried for five years and never knew whom to ask.
“These two questions are golden. They are what should be driving any AI project in the factory.”
Press··Smart Industry
Applied AI Labs Co-CEO Mike Fedorov joined Smart Industry’s Sarah Mattalian to unpack why so many AI projects miss the ROI they promise, and what mid-market manufacturers can do differently.
Mike Fedorov, Co-CEO of Applied AI Labs, joined Sarah Mattalian of Smart Industry on Great Question: A Manufacturing Podcast to discuss why so many AI implementations that are meant to improve business outcomes fail to produce meaningful ROI, and what manufacturers can do differently.
Mike and Sarah discussed three drivers of success that matter most for mid-market companies:
Solve the right problem.
Start with a tangible business issue, not with AI.
Start small.
Pick the simplest valuable problem and use it to build the organization’s muscles.
Work with the data you have.
Messy data can’t be ignored, but you don’t need to fix everything before starting.
“The measure of success isn’t whether AI works. It’s whether the business works better.”
Longer reads
Where a conversation raises something worth more than a podcast segment, we write it up properly — the argument, what it changes about how an operation is run, and how it shows up inside an engagement.
·7 min read·Quality During Design with Dianna Deeney
Your data will always be a little wrong. In interconnected operations, waiting for clean data means waiting forever — so the design question is not how to fix the inputs first, but how to build a system that tolerates, detects, recovers, and escalates.
Media & speaking
Our founders are operators first: 25+ years in supply chain and operations, ex-Accenture, ex-Mars, and serial AI founders. We are glad to go on the record, on a podcast, or in an interview.