Feedback Collection Automation on Datadog, Powered by AI
Run Feedback Collection on top of Datadog with an Arahi AI agent. Faster execution, fewer errors, zero manual busywork.
247 surveys sent · 3 detractors routed. Sample reply trigger:
Built in plain English.
You write the rule the way you'd describe it to a teammate. The agent reads the rule, breaks it into the actions it'll take, and confirms the apps it'll touch — before it does anything.
- 1Read the trigger event and pull the contact's context
- 2Draft the message in your team's voice
- 3Cite each personalized line's source
- 4Queue for your review or auto-send by confidence
Get started in three steps
Connect Datadog
Authorize Datadog and Arahi AI hooks into your issues, repos, and deployment pipelines.
Configure Dev Workflows
Define triggers for Datadog events — new issues, PR merges, build failures — and the AI actions to take.
Ship Faster with Less Toil
AI automates the tedious parts of your Datadog workflow. Track issues triaged, alerts handled, and developer time saved.
Saw your 4/10 — what would have made it a 9?
ChatGPT flagged your NPS reply for follow-up. You said the onboarding video was hard to follow — that's on us, and I'd love 10 minutes to walk you through the parts that bit.
Personalized using LinkedIn activity from the last 30 days.
Approve before it sends.
Every draft lands in a review queue. You approve, edit, or reject — the agent never acts on its own unless you explicitly turn that on for a workflow you trust.
Every action, with the reasoning attached.
Each step the agent takes is logged with what it did, why it did it, and which app it touched. Audit-ready, so security and compliance can sign off without backfilling.
- Marco11:42 AM
Approved the draft to alex@kibblecorp.com.
- Agent11:41 AM
Drafted the email and queued it for review.
Reason: High-confidence personalization but recipient is C-level — escalating per policy.
- Agent11:40 AM
Pulled LinkedIn activity and HubSpot deal context.
- Agent11:40 AM
Triggered: Send NPS surveys via @Datadog 30 days post-launch, route detractors to Customer
- Agent11:38 AM
Confirmed sender domain DKIM is healthy.
Frequently asked questions
Manual feedback collection in Datadog requires constant tab-switching, copy-pasting, and follow-up tracking. Arahi AI eliminates this by handling feedback collection tasks in real-time as Datadog events occur — running 24/7 with consistent accuracy and zero fatigue.
Yes. You can run feedback collection workflows in test mode using sample Datadog data before activating on live records. This lets you verify every feedback collection rule works correctly with your Datadog setup before processing real data.
All data exchanged between Datadog and Arahi AI during feedback collection processing is encrypted in transit and at rest. We use OAuth tokens for Datadog access, never store raw credentials, and maintain full audit logs of every feedback collection action.
No coding required. The no-code builder walks you through connecting Datadog and configuring feedback collection rules visually. Your team can set up, modify, and manage Datadog-based feedback collection workflows without any developer involvement.
The agent triggers surveys at the moment of peak feedback value — post-purchase, post-resolution, post-onboarding, or at datadog-specific lifecycle milestones. Timing is calibrated for highest response rate, not arbitrary monthly blasts.
Yes. The agent reads open-text feedback, identifies themes, scores sentiment, and surfaces operational issues that need attention — turning unstructured feedback into prioritized improvement workstreams for your datadog team.
Teams automating feedback collection through Datadog typically save 10-20 hours per week on manual processing. The ROI dashboard tracks time saved, tasks completed, and error reduction so you can quantify exactly what Datadog-powered feedback collection automation delivers.
Yes. You can create parallel feedback collection workflows that respond to different Datadog events or conditions. For example, one feedback collection flow for new Datadog records and another for updated ones — each with independent rules and actions.
Arahi AI connects natively with Datadog to handle the full feedback collection workflow. The AI agent monitors Datadog events, processes feedback collection tasks automatically, and writes results back to Datadog — no copy-pasting or tab-switching required.
Yes. You define exactly which Datadog events start feedback collection workflows — new records, status changes, messages, or custom triggers. Each trigger can have conditions so feedback collection actions only fire when your specific criteria are met in Datadog.
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