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Automatic retry, root-cause analysis and intelligent fallback handling — workflows that fix themselves.
Automatic retry, root-cause analysis and intelligent fallback handling — workflows that fix themselves.
Each pillar can be enabled, configured and audited independently.
Backoff, jitter, idempotency aware.
Swap to backup integrations.
Hypothesize, test, explain.
Rich incidents for true blockers.
Runbook self-update.
Schema, API, data changes flagged.
When a tool fails, an API rate-limits, or data is missing, agents diagnose, recover and retry — without paging a human at 3am.
Failures, timeouts, partial successes and data anomalies are detected at every step — not just at end-of-flow.
The platform classifies the failure: transient (retry), partial (compensate), data (re-fetch), structural (escalate).
Retry with backoff, switch to a fallback connector, re-fetch fresh data, scope down — pick the right recovery for the failure.
Where prior steps must be undone, recorded compensating actions are executed in reverse order.
Failure-recovery patterns feed back into the planner — flaky tools are de-prioritized, brittle paths flagged.
Real numbers from production deployments — across banking, healthcare, telco, manufacturing and the public sector.
Stop writing the same retry-and-fallback logic in every script. Self-healing is a property of the workflow runtime — agents inherit it.
Most production incidents are transient or data-driven. Self-healing absorbs them; humans see only the structural issues that actually need them.
Six concrete patterns from regulated enterprises across financial services, healthcare, telecom, public sector, energy and manufacturing.
On clearing-network glitches, agents retry, switch rails or compensate without paging operations.
On policy-admin downtime, claims agents queue and replay when systems recover, with full audit.
On payer-API failures, prior-auth agents retry, switch channels or escalate without losing the request.
On provisioning failures, agents retry, compensate, or escalate — orders don't get stuck.
On dependent-system outages, citizen-facing workflows queue resiliently and resume cleanly.
On plant-floor system issues, agents fall back to local edge stores and reconcile when central is back.
Production workflows fail. The interesting question is what happens next.
Hypothesis-driven, with evidence and confidence — surfaced for human review.
Yes — change proposals are reviewed before merge.
Most customers adopt new capabilities in 2-4 weeks through starter packs and onboarding workshops.
No. The capability runs on your existing xyner deployment — cloud, hybrid, on-prem or sovereign.
Yes — our customer success team and partners deliver guided migrations and pilots.
See xyner in your environment with a guided executive demo.