Support that keeps your lab running.
A lab platform is only as good as the support behind it. Labrynix backs your lab with a team that knows your setup, severity-based response targets, a clear escalation path, and training that continues long after go-live.
Urgent issues get urgent attention.
Not every issue is equal, and your support shouldn't treat them that way. Issues are triaged by severity, and the most critical ones get the fastest response.
System down
A core workflow is unavailable and the lab can't operate. These get the fastest response and continuous attention until service is restored.
Major impact
A key function is degraded or a workflow is significantly impaired, but the lab can still operate with a workaround.
Standard request
Questions, configuration changes, non-blocking issues, and how-to requests handled in the normal queue.
Response targets are set in your agreement
Severity levels describe how issues are prioritized. The specific response-time targets and any uptime commitments are defined in your service agreement, scoped to your plan and your lab's needs.
More than a help desk, a long-term partner.
A named team
You work with people who know your lab's configuration and integrations — not an anonymous queue starting from scratch each time.
Ticketing & tracking
Submit, track, and follow issues through to resolution, with severity and status visible the whole way.
Ongoing training
Role-based training and documentation that survive staff turnover, plus refreshers as your workflows evolve.
Continuous optimization
Support doesn't end at go-live — we keep refining workflows, automations, report templates, and integrations as your lab grows.
Release updates
Platform improvements and new capabilities are delivered on an ongoing cadence, with notes on what changed.
Escalation path
A clear escalation route for critical issues, so the most urgent problems reach the right people quickly.
Questions,
answered.
See how Labrynix supports labs like yours.
Named team · Severity-based response · Escalation path · Ongoing training · Optimization