Lower MTTR, less noise, and control over where it all runs
Condux groups errors precisely so your team sees signal, opens fix PRs to shorten MTTR, and runs in your own boundary under a source-available license. Seats are free and caps never surprise-bill you.
You care about signal, mean time to resolution and predictable cost. Condux is built around all three, and it lets you keep the whole loop, including the AI, inside your own infrastructure.
Less noise, more signal
- Precise grouping
Events fingerprint into deduplicated issues with exact per-hour counts.
- Alerts that fit the flow
Fire on new and regressed issues to email, Slack, Discord or a webhook, above a severity you choose.
- Verified resolution
After a fix merges, Condux watches the real stats and auto-resolves with evidence once the error stays silent.
Predictable cost
- Free seats
You are not taxed per developer to look at your own errors.
- Hard caps, not surprise bills
Caps throttle at the plan limit. Overage is an upgrade prompt, never an invoice shock.
- Transparent AI spend
Every fix run audits its real model token usage against a monthly allowance and a hard spend cap.
Control and compliance
Run the whole platform, including the fix agent, in your own boundary from one Docker Compose stack or a Helm chart. Bring your own model key so AI spend sits on your contract and no context leaves your network. Source-available code and a full audit trail mean your security team verifies the claims rather than trusting them.
Frequently asked questions
Can we keep everything in our own cloud?
Yes. Condux self-hosts under the FSL, and the Conductor runs on your own Anthropic or OpenAI-compatible key inside your boundary. The model never sees your repository token.
How does Condux keep cost predictable?
Seats are free, event and AI-fix limits are hard caps that throttle rather than overage-bill, and every AI run is metered against a monthly allowance and a per-org spend cap.