Is this not just enterprise search with AI?
A search layer or generic AI assistant does something genuinely useful: it searches the sources it can reach and formulates an answer. If finding information were the whole problem, that would be enough.
FixControl starts where the answer stops. It bounds information per project — a mailbox, channels, repositories, documentation you choose — and uses it to prepare actual work: an answer to a customer, a tested code change, a deployment step. And nothing meaningful leaves without checks and a recorded approval.
Three differences that matter
An assistant answers from all the sources it has access to. FixControl works per project with exactly the sources you attached — the invoicing question is answered with invoicing information, not with everything your organization ever wrote.
The output is not a chat message but a draft reply, a tested pull request or a prepared deployment step — ready for a person to review.
A search layer has no opinion about what happens with the answer. FixControl checks the rules and requires a recorded decision before an answer reaches a customer or a change reaches a repository.
When a search layer is enough
If your only problem is finding information — and no AI acts in your ticket system, repositories or deployments — a search layer or assistant serves you well. The moment AI starts preparing answers and changes in those systems, you need boundaries and approval around it.
See it on one real project
Connect your tickets, code or documentation, start read-only, and judge the difference on your own work. Guided onboarding proves each connection before you rely on it.
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