Castingwords

Connect DialNexa calls to Castingwords for model run, extraction result, generated answer, transcript, classification, media analysis, or tool call workflows.

CastingWords offers high-quality, human-powered transcription services with a RESTful API for seamless integration into various workflows.

Use Castingwords with DialNexa when the call needs classification, extraction, generation, retrieval, summarization, visual understanding, or another AI-assisted step.

Where Castingwords fits in a DialNexa workflow

Castingwords should receive DialNexa output when the conversation affects a model run, extraction result, generated answer, transcript, classification, media analysis, or tool call. The handoff should explain what the caller asked for, what DialNexa learned, which record or object is affected, and who owns the next step.

Extract structured details

Pull names, dates, products, addresses, invoice numbers, image labels, or requested actions into fields.

Keep humans in control

Send low-confidence, sensitive, or account-changing outputs to review instead of acting silently.

Classify call intent

Turn messy speech into intent, category, urgency, language, sentiment, and confidence fields.

Generate useful drafts

Create replies, notes, briefs, summaries, or tasks from the exact call outcome and approved context.

What DialNexa should capture for Castingwords

• Transcript, summary, language, speaker role, media or file link, intent, confidence, and sensitive-data flag
• Knowledge source, prompt version, model ID, tool call, allowed action, and fallback path
• Generated draft, extracted fields, recommended next step, review reason, and owner
• Transcript link, recording link, DialNexa call ID, CRM link, ticket link, and output record URL
• Risk flags for hallucination, missing source, private data, low confidence, or restricted action

High-value Castingwords workflows

Extract appointment or address details

DialNexa should capture the preferred time, timezone, owner, promise made, and contact channel before updating Castingwords. The receiving team should see exactly why the follow-up exists and what the caller expects next.

Summarize a long escalation

For this scenario, DialNexa should treat Castingwords as an escalation destination. Send the impact, urgency, affected customer or object, owner, and transcript link so the right team can act before the issue gets colder.

Answer from approved knowledge

For this workflow, DialNexa should send Castingwords a concise, action-ready handoff: matched caller, affected record, reason for the update, urgency, owner, next step, and links to call evidence.

Flag low-confidence AI output

For this workflow, DialNexa should send Castingwords a concise, action-ready handoff: matched caller, affected record, reason for the update, urgency, owner, next step, and links to call evidence.

Analyze call sentiment and urgency

For this workflow, DialNexa should send Castingwords a concise, action-ready handoff: matched caller, affected record, reason for the update, urgency, owner, next step, and links to call evidence.

Generate a follow-up brief for a human

DialNexa should capture the preferred time, timezone, owner, promise made, and contact channel before updating Castingwords. The receiving team should see exactly why the follow-up exists and what the caller expects next.

Classify support reason after calls

For this workflow, DialNexa should send Castingwords a concise, action-ready handoff: matched caller, affected record, reason for the update, urgency, owner, next step, and links to call evidence.

Use cancel and refund audio file

Treat cancel and refund audio file as a controlled workflow. DialNexa should capture the caller’s reason, identity confidence, approval owner, and rollback path before anything destructive or irreversible happens in Castingwords.

Use get transcript

Use get transcript before answering, routing, or creating follow-up. DialNexa should verify the lookup result against the caller and send low-confidence matches to a human queue.

Workflows that pair Castingwords with other integrations

• Castingwords + Slack: Slack for review of risky outputs.
• Castingwords + Google Docs: Google Docs for long-form call briefs.
• Castingwords + Notion: Notion for knowledge updates.
• Castingwords + Google Sheets: Google Sheets for extraction QA.
• Castingwords + Intercom: Intercom for customer conversation context.
• Castingwords + Google Drive: Google Drive for source files and recordings.

Implementation notes

• Use the DialNexa call ID as the idempotency key before running Castingwords actions.
• Write a short operational summary into Castingwords 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

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.

What should be logged for AI decisions?

Prompt version, source context, model or workflow ID, confidence, output, call ID, and reviewer when applicable.

How do we reduce hallucinations?

Use approved knowledge sources, cite source records, set fallback behavior, and route low-confidence answers to humans.

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.

What data should not be sent to AI tools?

Secrets, payment data, private HR or health details, and anything your policy forbids unless the tool and workflow are approved.

How should extraction errors be handled?

Store confidence and route missing or conflicting fields to review rather than silently updating downstream systems.