Automations
Trigger notifications, HTTP calls, and downstream updates when conversations reach defined states—closing the loop between chat and operations.
Automations turn successful—or failed—conversations into operations reality: notify #support-escalation, POST structured JSON to your scheduling service, or tag CRM opportunities when intent scores cross a threshold. Without this layer, chat stays a sideshow instead of part of how work moves.
FlexyAgents exposes a shared automation builder across customer, sales, and internal agents so you standardize patterns instead of maintaining one-off Cloud Functions per team.
Payloads should include conversation IDs, customer identifiers your backend expects, and minimal PII—mask where policy requires.
Retries with exponential backoff handle transient 503s; dedupe keys prevent double bookings when a webhook fires twice.
Log request and response codes in observability stacks you already use.
Channel messages should summarize what the bot tried, what it found, and why it escalated—links back to transcripts help responders start fast.
Role mentions should be intentional; noisy bots get muted.
Separate channels for sales, support, and internal IT reduce alert fatigue.
Tell customers when a downstream system is down; do not pretend a booking succeeded if the API never returned 200.
Queue automations when possible so brief outages do not lose intent.
Fall back to ticket creation when webhooks fail repeatedly.
Automation credentials should be scoped to the minimum API actions required.
Review automation changes in change management like any production config.
Disable risky automations quickly with feature flags during incidents.
Explore the platform
See platform features, browse templates, compare pricing, or contact sales.
More from the blog—starting with the same category as this piece.
Sync docs, tickets, and commerce data so your knowledge base chatbot and AI FAQ for help centers answer from real content—not guesses.
Read articleBYOK (bring your own key) lets enterprises use their own model provider keys inside an AI control plane—with governance, metering, and procurement alignment.
Read articleGround AI customer support in approved content, monitor conversations, and apply governance so your assistant stays accurate and reviewable.
Read articleNext step
Start a trial, book a walkthrough, or talk to us about governance and rollout—same workspace for pilots and production.