Know where your AI needs attention.
Surface unresolved requests, missed handoffs and policy concerns across your agents. Route the finding and its context to the team responsible for the response.
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Example data| Rule | Status | Severity | Channel | Assistant |
|---|---|---|---|---|
| Open | High | Call | Service appointments | |
| Open | Medium | Call | Service appointments |
Open a finding to review the conversation behind it.
Powering businesses, agencies and franchise operators.
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Make a missed handoff visible.
A caller asks for a person, but leaves without a clear handoff. An Observation connects that exchange to a review your team can act on.
Define the condition
Describe an unaddressed request for human help. Set the rule’s conversation scope, category and severity around your operating process.
Review the finding
Evaluate the conversation against that rule. Inspect the recorded explanation and supporting context to understand why it was flagged.
Route the response
Send triggered alerts to the configured Slack, email or webhook destination. Give the responsible team a focused starting point for follow-up.
Spend review time where it matters.
Recover an unresolved request
Identify conversations that need a person to close the loop, from an unanswered appointment question to a service complaint.
Apply your own standards
Monitor the disclosures, escalation behavior and business-specific conditions that matter to each agent’s role.
Spot the recurring issue
Bring related findings together so the team can improve an instruction or process instead of handling each occurrence in isolation.
A useful alert has a clear owner.
Connect each monitoring rule to the attention and action it deserves.
Tune the signal
Use matching and non-matching conversations to refine the rule. Severity filters, thresholds and cooldowns keep notifications focused.
Assign the response
Choose the destination and team for each type of finding. Review notification history alongside the underlying conversation evidence.
Separate detection from enforcement
A finding identifies something to review. An opt-out or escalation still needs the appropriate action in the receiving system.
Product capabilities and architecture
Assistable Observations evaluates voice and chat conversations against rules your team defines. It records findings and routes triggered alerts through Slack, email or webhooks, giving operations teams a focused way to monitor conversation quality and escalation needs.
Your standards, applied across your agents.
- Rules in your own language
- Describe the behavior that matters: required disclosures, unclear outcomes, escalation requests or a business-specific condition. Keep the standard tied to how your operation works.
- Account and assistant coverage
- Combine common standards with checks tailored to individual roles. Sales, scheduling and support agents can share foundational rules while keeping their own review criteria.
- Alert controls that respect attention
- Set severity, trigger thresholds, time windows and cooldowns. Filter alert destinations by minimum severity so the appropriate team sees the appropriate signal.
- Evidence behind the alert
- Inspect the evaluator result, extracted information and associated conversation evidence. Notification history provides context on the alerting activity recorded for the finding.
From conversation evidence to an operational response.
Connect each finding to its rule, conversation evidence and responsible team.
- Structured evaluation
- The rule and conversation evidence produce a recorded finding with an explanation reviewers can assess.
- Connected alert destinations
- Send findings to email or Slack, or use a webhook to start a configured downstream process.
- A foundation for improvement
- Group recurring findings into issues and candidate fixes, keeping the proposed change connected to its source.
Operating controls and references
Clear rules. Clear ownership.
Make monitoring part of a defined operating process, with a responsible team for each type of finding.
- Tune the signal
- Use representative matching and non-matching conversations to refine a rule. Review false positives and adjust the instruction as the process changes.
- Connect detection to the required action
- An opt-out finding can trigger a downstream process. The receiving system must complete the suppression action; sending an alert alone does not change a contact preference.
- Choose approved destinations
- Control who receives conversation information. Match evaluation timing and alert routing to the channel and the response your team needs.
Observations
questions.
What can an observation rule detect?
A rule can evaluate a specific condition described by your team, such as a missed disclosure, unresolved request or escalation need. Its recorded finding can include severity, an explanation and extracted context.
Can we send AI conversation alerts to Slack?
Yes. Rules support Slack, email and webhook destinations, with severity filters, thresholds and cooldowns. Different findings can go to different owners.
Does Observations cover voice and chat?
Rules can target calls, chat or both. Evaluation checkpoints and available evidence depend on the channel and deployment. The timing should match the response you need.
How should our team use an AI-generated finding?
Use it to prioritize and inform review. No evaluator guarantees that it will detect every problem. Clear rules, representative examples and human assessment make the findings more useful.
Define what your team needs to catch.
Bring your quality standards and escalation process. We’ll map the rules, evidence and alert destinations around them.
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