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Channel Ingestion Setup

Conversation Analytics relies on having conversation content (audio or text) plus consistent metadata (participants, timestamps, channel, queue/team, etc.).

This chapter describes how a platform operator should set up and validate ingestion across channels.

Ingestion goals (operator)

  • Ingest conversations reliably and securely.
  • Normalize metadata so reporting, filtering, and AI Tasks behave consistently.
  • Detect ingestion gaps early (monitoring/alerts).

Supported channel types (conceptual)

Voice calls (speech)

Typical inputs: - audio recording(s) - call metadata (direction, start/end time, agent ID, phone numbers, queue/campaign)

Outputs to downstream pipelines: - raw audio + normalized metadata record

Text channels (omni-channel)

Typical inputs: - chat transcript / message thread - email thread (messages + headers) - ticket thread (comments, updates, resolution status) - metadata (agent/customer IDs, timestamps, channel, queue, tags)

Outputs to downstream pipelines: - normalized text thread + metadata record

Note: Even in text channels, the “conversation” is treated as a single analyzable unit with a thread of messages/events.

Define and enforce a standard schema so everything downstream can rely on it.

At minimum, capture:

  • Tenant ID
  • Conversation ID (stable)
  • Channel type (call/chat/email/ticket)
  • Start/end timestamps
  • Participants
  • agent identifier
  • customer identifier (if available)
  • Direction (inbound/outbound), where applicable
  • Queue/team/campaign (optional but strongly recommended)
  • Language (optional; transcription/AI may infer)
  • Tags / dispositions (optional)

Validation checks (before enabling analytics)

For each channel: - ✅ content is present (audio or text thread) - ✅ metadata fields are populated and consistent - ✅ IDs are stable (no duplicates) - ✅ timestamps are correct (time zone handling) - ✅ sample conversations appear in the UI for the intended tenant

Operational best practices

  • Backfill support: Ensure you can ingest historical conversations for onboarding and reprocessing.
  • Deduplication: Protect against duplicate ingestion events.
  • PII handling: Decide whether redaction happens pre-ingestion or inside MiaRec pipelines (document the chosen approach).
  • Error handling: Use retries and a dead-letter strategy for poison messages.
  • Observability: Monitor ingestion throughput, latency, and error rates per tenant and channel.

Implementation notes

MiaRec supports various voice ingestion methods including:

  • SIPREC / PBX recordings
  • CCaaS integrations (Genesys, NICE, Five9, Amazon Connect, etc.)
  • Upload via API

For text channels (chat, email, tickets), support varies by deployment. Contact MiaRec for details on specific connector availability.

  • Document a minimum required metadata schema and a "recommended schema"
  • Strongly recommend stable conversation IDs and tenant IDs
  • Provide sample payloads (voice + text) and validation steps