Turn your scripts into internal tools.
Upload a Python, shell or Node script, and Reminix runs it. Start it from a form, the API or the CLI. Let it run on a schedule or from a webhook, or hand it to your AI agents.
Visit reminix.comOmsome builds products for teams that write software with AI, and works with a small number of selected partners on product research and engineering.
We build and run focused products for teams shipping software with AI. Two are live today.
See the productsProduct research and engineering for a small number of selected partners, agreed in writing and led by the same team.
How partnerships workWe research before we build, keep every product small and its promises firm, and engineer with AI at every step.
About OmsomeThat is the work Omsome does: in the products we build and run ourselves, and with the partners we work alongside.
Built and run by Omsome. Each one does a single job, completely.
Upload a Python, shell or Node script, and Reminix runs it. Start it from a form, the API or the CLI. Let it run on a schedule or from a webhook, or hand it to your AI agents.
Visit reminix.comGive each of your users, teams, API keys or agents an allowance, like a $2 AI budget a month or 60 requests a minute. Limitry says yes or no before each costly request. Your code then calls your providers directly.
Visit limitry.comEach product does a single job end to end, and leaves the rest to the tools teams already use.
Every product has a short list of promises it never breaks, and every plan is checked against them.
We also write down what each product will never become, so it stays focused as it grows.
Our products rely on each other, through the same public APIs and documentation as any customer.
The same team that builds our products takes on a small number of partner engagements each year: product research, technical exploration and focused software engineering, under a written agreement.
How partnerships workClarify the problem, study the people and workflows around it, and name the assumptions that need evidence before anyone builds.
Prototype the uncertain parts, including what AI makes newly possible, and decide what is feasible and worth doing.
Test the product direction and the riskiest assumptions before a full build turns uncertainty into an expensive commitment.
Bring AI into an existing product with costs held to a budget, keys kept out of the code, and people in charge of what agents may do.
Work through hard choices about scope, interaction and technical direction, including what the first version must refuse to do.
Design and build focused software with a small, senior team, carried from decision to delivery and handed over properly.