We're building automation that works like a good coworker.
Good coworkers follow instructions, use judgment where it's needed, and own the details. So does Lodol.
Why Lodol
Automation touches the invoices, payments and records a business runs on. That asks for a lot of trust.
Too many tools don't earn it. They dazzle in the demo and stumble under real work, and the hours they save in the morning go to cleanup in the afternoon.
AI has made automations easier than ever to build. Running them is the hard part: on every trigger, with keys kept safe and every run on the record. That's the job we built Lodol to do.
Reliability comes first
It's the north star behind every decision we make. Four principles hold us to it.
The same steps, every time
A workflow is a fixed set of steps that runs the same way on every trigger. AI is involved only at a step that asks for it.
A record of every run
Every run is recorded step by step, so you can open any one and see exactly what happened.
A person in the loop where it matters
A run can wait for someone's approval, and anything a workflow isn't sure about can go to a person instead of a guess.
Changes you can undo
Try a workflow before you switch it on, compare it with any earlier version, and roll back in a click.
The team
A small team, on purpose, with backgrounds from places like Stanford, Amazon, Orby AI and Yale. Whoever builds something here owns how it lands.
Co-Founder & CEO
Built mission-critical automation for global enterprises as a founding engineer at Orby AI. Studied AI at Stanford, was a visiting researcher at the University of Washington and subcontracted for the U.S. Air Force.
Co-Founder & President
Advised and backed AI-first startups across stages, drawing on experience in venture capital, family offices and startup growth. Studied product design at Stanford.
Machine Learning Engineer
Led strategic AI pilots at Abacus.AI and managed a data science team at Loxz Digital Group that significantly improved forecasting accuracy. Studied AI at Stanford.
Backend Engineer
At Amazon, built software for the custom chips used across the AWS network, along with the automated tests and performance alarms that watch over it. Studied AI at Stanford.
Senior Software Engineer
Spent more than five years building AI applications and cloud platforms across healthcare, sales intelligence, real estate and SaaS. Has shipped products powered by LLMs, AI agents and semantic search.
Designer
Designed web and mobile products for fintech, healthcare and aviation, from startups to large organizations. Has worked across the whole design cycle for more than five years, from first idea through launch and long-term support.
Software Engineering Intern
Created statistical modeling frameworks for quantum computing analysis at Yale's Quantum Institute. Built data analytics tools for high-performance computing clusters at the Wu Tsai Institute.
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Put Lodol to work
Build your first workflow today, or talk with our team about the work you want to hand off.