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Real stakes, real curiosity

Research systems, decision engines, adversarial analysis — AI built to survive contact with reality.

Most things built with AI peak at the demo stage. The interesting work lives where autonomy meets accountability. Systems that make decisions, not suggestions. Research that compounds. Analysis that holds up when real money is on the line.

Active questions
The interesting work rarely stops at the model. It runs through markets, institutions, incentives, coordination, and people under real constraints. Here's what we're thinking about right now:
What we do

Flowalto builds infrastructure, not advice. The work is production code — API layers, streaming systems, model orchestration, agent tooling, database architecture — not prompt libraries or workflow diagrams repackaged as strategy. When a team needs AI wired into live operations, the deliverable is software that runs: services that handle concurrency, manage context, normalize across providers, and fail gracefully under load.

Engagements are selective and the work is hands-on: protocol design, tool surfaces, execution control, storage layers, review layers, and the rules that govern how software behaves under real conditions. Alongside that work, we build our own products with the same discipline. The interesting work is rarely in the demo. It is in the architecture that keeps working after one.

From the lab

Zwischen

Zwischen adds a second, adversarial AI to catch bad code, risky edits, and made-up facts before they go out.

Visit zwischen.ai Read the blog

What are you thinking about?

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