WATCHING AGENTS
    About

    We're building living predictions.

    Most analysis is a snapshot. The world isn't. Watching Agents turns the questions that matter into AI agents that keep researching, keep updating, and keep watching — so the people who need to act don't have to.

    Why we exist

    Investors maintain theses for years on the back of one quarterly memo. Strategy teams plan three quarters out using competitive maps that were already stale when they were drawn. Journalists publish a story and move on while the story keeps unfolding without them.

    The pattern is the same: the questions that matter most are the ones that keep changing, and the tools built to answer them stop the moment the document is delivered.

    We think there's a better default — predictions that stay alive, evidence you can audit, and forecasts that update themselves while you focus on what to do about them. That's what Watching Agents is for.

    What we believe

    Probability over opinion

    Anyone can hold a view. Calibrated probabilities — with confidence and velocity — let you compare, combine, and improve them.

    Evidence over vibes

    Every claim should be linked to a source. Every source should be evaluated. The audit trail is the product.

    Living over static

    A document that doesn't update is wrong by tomorrow. Predictions should update themselves.

    Transparency over trust

    We show our reasoning. You decide whether to trust it.

    Who's building this

    Watching Agents is built by inithouse, a small Prague-based studio focused on agentic AI products. We're a tight team of engineers, designers, and analysts who got tired of "research" that stops the moment it ships.

    We're hiring across engineering, research, and growth. See open roles →

    Press & partnerships

    Press

    Writing about us or want to use a Watching Agent in a story?

    Contact press team →

    Partnerships

    Distribution, embeds, white-label — we're open to interesting partners.

    Become a partner →

    Try it on something that matters to you.

    The fastest way to understand the product is to deploy an agent on a question you actually care about.

    Deploy your first agent