Use case

AI exploratory testing, with evidence

Exploratory testing is how experienced QA engineers find the bugs scripts miss. Locodera turns that instinct into an autonomous agent that can run before every deploy.

Last updated October 31, 2026

Who this is for

QA engineers and product teams who value exploratory testing but cannot scale it manually.

The problem

  • Exploratory sessions are valuable but inconsistent.
  • Notes and screenshots are scattered across tools.
  • A single observation may be a fluke, not a bug.

How Locodera handles it

  1. 01

    Persona goals

    New, returning, paying, frustrated, mobile and admin users each explore differently.

  2. 02

    Edge cases

    Empty inputs, long strings, special characters, double submits, reloads and history navigation.

  3. 03

    Replay

    The verifier repeats the exact actions in a clean context.

  4. 04

    Evidence

    Screenshots, video, console and network errors are attached to confirmed findings.

Relevant capabilities

Six personas

New, returning, paying, frustrated, mobile and admin users.

Edge cases

Empty inputs, long strings, double submits, reloads and history.

3/3 verification

Only findings that reproduce every time are confirmed.

Evidence

Screenshots, video, console and network logs per attempt.

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FAQs

How is this different from manual exploratory testing?+

It runs automatically, records every action, and repeats the session to distinguish a real bug from a one-off.

Can I guide the exploration?+

V1 focuses on autonomous personas and edge cases; test credentials and the target URL are configurable.

Do I get repro steps?+

Yes. Confirmed issues include the steps Locodera performed and the reproduction rate.

Find the bugs your tests never looked for.

Add your app, run an exploratory scan, and get a release verdict backed by evidence.