Software is being written faster than it is being checked.
That imbalance is the whole reason BugLight exists. This page is the long version: the shift we are building against, what is real today, and what we think this becomes.
Why now
AI tools have changed the rate at which software gets produced. More code is written, in less time, by teams the same size they were before. That part is visible to anyone who has shipped in the last two years.
Verification did not move with it. Deciding what to test, writing the tests, running them, and keeping them current as the product changes underneath is still manual work done by people who could be building instead. So a gap opens: generation accelerates, checking does not, and the amount of shipped software that nobody has really examined grows every release.
The usual response is to write tests faster, which is the same work with a shorter deadline. BugLight is built on a different reading: if code production has become autonomous, verification has to become autonomous too, or it simply becomes the place every release waits.
That is a thesis, not a measurement. We are not going to put a number on this page that we cannot stand behind.
Shipped, being built, and where it is headed
These three are kept apart on purpose. Nothing in the second or third column is something BugLight does for you today.
Available today
- API testing from an OpenAPI or Swagger specification and a target URL
- Endpoint discovery, scenario generation, execution, and response validation
- Status codes, response schemas, error handling, boundary and edge cases, rate limiting, and timeout behavior
- An AI-driven browser agent that explores a running web application and reports what it finds
- Security testing, working the same application from the outside and reporting into the same place
- An AI layer that can work with local models
In development
- Deeper analysis of why a run failed rather than only that it failed
- Running all three methods against one application as a single coordinated pass
Where this is going
- BugLight learning a company's own context: requirements, acceptance criteria, architecture documentation, past results, past bugs, and past fixes
- Moving from whether software technically works toward whether it behaves the way this company defines correct
- A quality layer that gets more specific to a company the longer it runs there
From “does this work?” to “is this right for us?”
Today BugLight analyzes software and detects technical problems. It can tell you that an endpoint accepts a value it should have rejected, or that a checkout flow completes when it should have stopped.
What it cannot do is know that your organization decided, in a requirements document eighteen months ago, that this particular behavior is intentional. Every engineering team carries that kind of context, and almost none of it is available to the tools doing the checking.
The direction we are building toward is a system that learns that context: product requirements, acceptance criteria, architecture documentation, historical test results, bugs found before, and how they were fixed. The more of a company’s own material BugLight understands, the more specific its judgment about that company’s software can become.
That is the long-term shape: not a test runner, but a quality layer that knows what correct means in one particular company. None of it exists yet, and nothing on this site presents it as if it does.
The founding team
BugLight is early, and it is being built by four people who would rather show you the product than talk about it.
- Alper Solmaz
- Bengü Özbek
- İrem Cengiz Solmaz
- İzzet Ahmet
Bring us something you have not had time to test.
An API with a specification, or a web application we can reach. We will run BugLight against it and walk you through whatever it finds, including the runs where it finds nothing.