Releasing fast shouldn’t mean breaking things. As your product grows, Ogoron takes over your QA process end‑to‑end. It understands your product, generates and maintains tests, and continuously validates every change - replacing a systems analyst, test analyst, and QA engineer. Get predictable releases, fewer bugs in production, and full coverage without manual effort. Ship faster. Stay in control. Break nothing
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How „smart“ is the analysis? Does it really understand business logic? We have complex financial rules - would love to know how deep it goes.
Ogoron
@sevryukov_vs Good question. The analysis can go fairly deep when the business logic is actually expressed in the artifacts available to the system — code, product behavior, specs, and provided documentation.
If the rules are complex but still fairly standard for the domain, modern models are often much better at reconstructing them than people expect. We were honestly surprised ourselves by how much sensible structure they can extract directly from code.
That said, we try to stay realistic: if critical business logic is not recoverable from the available sources, Ogoron should not pretend to understand it perfectly. In those cases, trustworthy grounding and user clarification still matter
Curious how it handles edge cases and unexpected flows .That’s usually where automated QA tools start to break down.
Ogoron
@francis_dalton Very fair point – edge cases and unexpected flows are exactly where automated QA usually starts to get real.
Our view is that the goal is not to pretend everything is expected. It is to recognize when the system is operating inside a high-confidence pattern, and when it is not. When Ogoron can reliably interpret the situation, it handles it automatically; when it cannot, it surfaces the ambiguity instead of forcing a false answer.
A big part of the product is continuously expanding that high-confidence zone. In practice, many "unexpected" cases are not unique at all – they are recurring patterns that different teams have already run into in one form or another. A lot of the work is turning more and more of that real-world experience into something the agent can recognize and handle safely
Congrats!
Can I opt out of any data sharing for product improvement? We can't allow any data to leave our network
Tnx!
Ogoron
@konstantinkz Thanks – in the standard managed setup, some data does pass through our infrastructure, and requests currently also go to OpenAI as the external LLM provider.
So if your requirement is that absolutely no data leaves your network, we should be transparent: we do not fully support that today. We can discuss deployment on your own infrastructure, but external LLM calls still remain part of the current architecture
I honestly don’t really get it, but no matter how much I look at TDD, I can’t seem to understand it. Should it be done before the code review stage, or after code review, just before the final product check?
Ogoron
@adamspong Thanks for the question. To clarify, Ogoron is not about strict TDD in the classic sense. It is an automated QA system that generates, maintains, and runs tests as the product evolves.
In most workflows, that fits before code review: when a branch is ready, tests are refreshed, smoke checks run on pushes, and the broader suite can run before review or merge
That's great! Does it require any special permissions or firewall rules?
Ogoron
@anna_drobysheva Good follow-up question.
No special firewall rules are required beyond normal outbound access for the CI job. The main thing is that the runner can reach our services and the OpenAI API.
On the permissions side, it is also fairly standard: repository access, and if you want automated change flows, permission to commit or create changes back into the repo.
We also support file-level allowlisting, so if there are parts of the repository or configuration you want to keep outside the agent’s scope, that can be restricted
How quickly can I get help if the integration fails? Our release is time‑sensitive
Ogoron
@daniil_kadeev Thanks – very important question.
A big part of the value here is that Ogoron generates tests which can then be used independently of Ogoron itself. We also do not restrict running those tests through Ogoron, and test execution remains free, so this part of the workflow is not something we want teams to feel locked into or blocked on.
For early users, we are also quite hands-on with integration support. If something blocks setup or rollout, we usually help directly and quickly rather than leaving the team to handle it alone
Is there an official GitLab CI template or example .gitlab-ci.yml snippet?
Ogoron
@astepanov Thank you for your question – yes, we already have example snippets for several common GitLab CI setups in our docs at docs.ogoron.ai.
If your pipeline is a bit more specific, we can usually help adapt a template for it fairly quickly.
The main caveat today is that GitLab is not yet fully supported through the self-serve dashboard: repository connection there is still GitHub-first. But if you want to test Ogoron with GitLab, feel free to reach out to me or Nick for early access