Solutions

The right message.
Every time. For everyone.

A single pipeline failure affects five different teams in five different ways. Fanal writes five distinct messages — no technical jargon for finance, no fluff for engineers.

Data engineers

Stop writing incident Slack messages.

Fanal handles the full communication loop. You get the stack trace, the root cause hypothesis, and the debugging step. Everyone else is notified automatically — you focus on fixing.

What you get

  • → Stack trace + root cause hypothesis
  • → Full lineage blast radius map
  • → Pre-incident warnings before failure
  • → Auto-generated postmortem in Notion
  • → Historical incident RAG for faster resolution

What you get

  • → Which dashboards are wrong and since when
  • → Which specific metrics are affected
  • → ETA for resolution — no chasing engineers
  • → Zero technical jargon in your notification

BI analysts

Know before your stakeholders ask.

Fanal tells you exactly which dashboards are showing stale data, which specific metrics are affected, and gives you an ETA — all before anyone asks why the numbers look wrong.

Finance teams

Revenue at risk. In plain English.

No table names. No error codes. Just the business impact, the estimated dollar figure, who owns the fix, and when it will be resolved.

What you get

  • → Which reports are affected
  • → Month-close and board pack risk assessment
  • → Estimated revenue impact in dollars
  • → ETA and escalation status

'The APAC revenue pipeline failed at 03:14 UTC. Your Monday board report will be missing Friday-Sunday APAC data. Estimated impact: $47,000. Engineering is resolving. ETA: 2 hours.'

FANAL COORDINATOR AGENT · EXAMPLE OUTPUT

What you get

  • → Which models ingesting bad data right now
  • → Live serving endpoint status
  • → Recommendation on whether to pause predictions
  • → Data drift description

ML teams

Know when your models are training on bad data.

Fanal identifies which ML models are consuming data from affected pipelines, whether they have live serving endpoints, and whether predictions should be paused.

Every team. One platform.

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