> ## Documentation Index
> Fetch the complete documentation index at: https://dialnexa.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Astica AI

> Connect DialNexa calls to Astica AI for record, request, case, lookup, approval, workflow run, or operational task workflows.

astica ai offers a suite of cognitive intelligence APIs, including computer vision, natural language processing, and voice synthesis, enabling developers to integrate advanced AI capabilities into their applications.

<Note>
  Use Astica AI with DialNexa when the call creates a specialized follow-up that needs owner, urgency, and clear operational context.
</Note>

## Where Astica AI fits in a DialNexa workflow

Astica AI should receive DialNexa output when the conversation affects a record, request, case, lookup, approval, workflow run, or operational task. The handoff should explain what the caller asked for, what DialNexa learned, which record or object is affected, and who owns the next step.

<CardGroup cols={2}>
  <Card title="Build review queues" icon="check-circle">
    Hold unclear, sensitive, high-value, or low-confidence cases for human review.
  </Card>

  <Card title="Measure recurring issues" icon="check-circle">
    Tag repeated call reasons so operations can see where customers keep getting stuck.
  </Card>

  <Card title="Create structured handoffs" icon="check-circle">
    Capture caller identity, request, affected object, owner, urgency, and decision needed.
  </Card>

  <Card title="Route niche requests" icon="check-circle">
    Send specialized calls to the person who knows the system, product, policy, or customer context.
  </Card>
</CardGroup>

## What DialNexa should capture for Astica AI

* Caller identity, account, source, owner, category, urgency, and related object ID
* Call summary, requested outcome, missing information, blocker, and promised next step
* Status, priority, deadline, approval requirement, duplicate key, and review reason
* Transcript link, recording link, DialNexa call ID, CRM link, ticket link, and file links
* Sensitive-data flag and routing note for human review

## High-value Astica AI workflows

<AccordionGroup>
  <Accordion title="Low-confidence match needs review">
    For this workflow, DialNexa should send Astica AI a concise, action-ready handoff: matched caller, affected record, reason for the update, urgency, owner, next step, and links to call evidence.
  </Accordion>

  <Accordion title="Owner should be alerted quickly">
    For this workflow, DialNexa should send Astica AI a concise, action-ready handoff: matched caller, affected record, reason for the update, urgency, owner, next step, and links to call evidence.
  </Accordion>

  <Accordion title="Caller creates an operational request">
    For this workflow, DialNexa should send Astica AI a concise, action-ready handoff: matched caller, affected record, reason for the update, urgency, owner, next step, and links to call evidence.
  </Accordion>

  <Accordion title="Specialist review is required">
    For this workflow, DialNexa should send Astica AI a concise, action-ready handoff: matched caller, affected record, reason for the update, urgency, owner, next step, and links to call evidence.
  </Accordion>

  <Accordion title="Missing information blocks progress">
    DialNexa should attach the relevant file or visual evidence, summarize what the caller says it proves, and mark the review owner in Astica AI. Sensitive files should stay behind restricted links.
  </Accordion>

  <Accordion title="Approval is needed before action">
    For this workflow, DialNexa should send Astica AI a concise, action-ready handoff: matched caller, affected record, reason for the update, urgency, owner, next step, and links to call evidence.
  </Accordion>

  <Accordion title="Recurring issue should be categorized">
    DialNexa should write the symptom, expected behavior, actual behavior, affected area, business impact, and evidence links into Astica AI. A teammate should be able to triage the issue without replaying the call.
  </Accordion>

  <Accordion title="Use analyze audio">
    Use analyze audio when the call outcome maps clearly to that operation and the required fields, owner, review state, and evidence links are known.
  </Accordion>

  <Accordion title="Use astica read text">
    Use astica read text when the call outcome maps clearly to that operation and the required fields, owner, review state, and evidence links are known.
  </Accordion>
</AccordionGroup>

## Workflows that pair Astica AI with other integrations

* [Astica AI](/integrations/astica_ai) + [Google Calendar](/integrations/googlecalendar): Google Calendar for scheduled callbacks.
* [Astica AI](/integrations/astica_ai) + [HubSpot](/integrations/hubspot): HubSpot for customer context.
* [Astica AI](/integrations/astica_ai) + [Slack](/integrations/slack): Slack for owner alerts.
* [Astica AI](/integrations/astica_ai) + [Google Sheets](/integrations/googlesheets): Google Sheets for review queues.
* [Astica AI](/integrations/astica_ai) + [Zendesk](/integrations/zendesk): Zendesk for support follow-up.
* [Astica AI](/integrations/astica_ai) + [Google Docs](/integrations/googledocs): Google Docs for operational briefs.

## Implementation notes

* Use the DialNexa call ID as the idempotency key before running Astica AI actions.
* Write a short operational summary into Astica AI and link to the full transcript or recording for audit.
* Map required fields before launch: destination object, owner, status, urgency, next step, and record URL.
* Create review paths for low-confidence matches, sensitive requests, high-value customers, and actions that change money, access, legal terms, or customer commitments.

## FAQs

<AccordionGroup>
  <Accordion title="How should extraction errors be handled?">
    Store confidence and route missing or conflicting fields to review rather than silently updating downstream systems.
  </Accordion>

  <Accordion title="When should an AI answer fall back to a human?">
    When source context is missing, confidence is low, the caller disputes the answer, or the next step changes money, access, or legal commitments.
  </Accordion>

  <Accordion title="What should be measured over time?">
    Intent accuracy, extraction accuracy, fallback rate, review overrides, bad answers, and customer outcomes after AI-generated follow-up.
  </Accordion>

  <Accordion title="Should AI outputs act without review?">
    Only for low-risk workflows with clear confidence thresholds. Account changes, money, access, legal, and sensitive support cases need review.
  </Accordion>

  <Accordion title="What should be logged for AI decisions?">
    Prompt version, source context, model or workflow ID, confidence, output, call ID, and reviewer when applicable.
  </Accordion>

  <Accordion title="How do we reduce hallucinations?">
    Use approved knowledge sources, cite source records, set fallback behavior, and route low-confidence answers to humans.
  </Accordion>

  <Accordion title="Can DialNexa write follow-up messages with AI?">
    Yes, but drafts should use the actual call outcome, approved tone, and customer context. Sensitive messages should be reviewed.
  </Accordion>
</AccordionGroup>