Kismet is an experimentation platform where anybody can ship design-heavy and code-heavy experiments quickly. Variants come from a prompt and from the company’s own design system, so they look native. They match the codebase you already have.
Kismet opens a pull request that wraps the change in a flag and adds instrumentation. It suggests metrics and guardrails, runs a power calculation, and flags collisions with experiments that are already running.
After it is live
Kismet does the QA and the monitoring: automated exposure checks, sample ratio mismatch detection, and alerts. When an experiment ends, it writes a plain-language readout and files it in a searchable library, so the team does not retest the same idea.
Smaller samples
Most experimentation tools assume consumer-scale traffic. Kismet is also for teams with less of it: sequential testing, Bayesian methods, bandits, and informative priors from past experiments. The detail is packaged, and the surface is simple enough that anyone on the team can use it.
Where the ideas come from
Most teams still rank ideas with ICE scores in a spreadsheet, which is mostly gut feel. Kismet mines analytics, session replays, support tickets, and past experiment results, and proposes a hypothesis with a rough estimate of impact.
It can also predict platform usage, and usage of a specific feature, from click-through and the other statistics you already collect.