ChatAman Docsby CodeEra
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AI Settings Explained

Configure models, response behavior, conversation memory, orchestration, distribution, and safe handoff behavior.

CodeEra AI agent builder inside Chataman CodeEra AI agent builder inside Chataman
CodeEra AI agent builder inside Chataman

API configuration

  • OpenAI API Key: secret used by this organization. Leaving the field empty keeps the saved key.
  • Organization Key: optional OpenAI organization identifier when your account requires one.
  • Model: model used for customer replies and agent decisions. Use the configured default unless you have tested another supported model.
  • Max Tokens: maximum generated response size. Higher values may increase latency and cost.
  • Temperature: creativity level. Customer support normally benefits from a lower, more consistent value.
  • Timeout: how long Chataman waits for the provider before treating the request as failed.

Voice settings

  • Voice transcription model: converts voice notes to text. The default is optimized for fast, cost-effective transcription.
  • Speaker diarization: identifies different speakers in longer recordings. Enable it for calls or multi-speaker audio, not every short voice note.

AI features

  • Chat Completion: allows generated conversational replies.
  • Conversation History: includes recent messages so the reply follows the current context.
  • Information Extraction: pulls structured facts from free text.
  • Sentiment Analysis: detects tone and intent for routing and reporting.
  • Content Moderation: helps block unsafe or policy-violating content.
  • Auto Reply: allows automatic customer replies. Enable only after controlled testing.
  • Auto Sentiment Analysis: analyzes every eligible incoming message.

Conversation and cost controls

  • Max History Messages: number of recent messages passed to the model. More context can help, but increases token use.
  • Cache Duration: how long reusable AI results remain cached.
  • Confidence Threshold: minimum confidence expected before automated behavior is trusted.
  • Daily Request Limit / Monthly Token Limit: spending and usage guardrails for the organization.

Orchestration modes

  • AI First: AI makes the main decision and may invoke flows as sub-routines.
  • Hybrid (Recommended): active matching flows continue; otherwise AI handles the conversation.
  • Flow First: flows take priority and AI responds only when no flow is active.

Handoff and distribution

  • AI Can Close Ticket: lets AI close a ticket when the goal is clearly complete. Keep off until your close rules are tested.
  • Summary on Human Handoff: adds a short context summary for the receiving agent.
  • Continue Active Flow First: lets an active flow finish its current path before AI takes over.
  • Wait for AI / Flow Handoff: does not assign a human at conversation start.
  • Distribute from the Start: legacy behavior that assigns a human immediately.
  • AI Decides First: gives AI a clean opportunity to answer, run a flow, or escalate before human assignment.
  • Max open chats per agent and Office Hours: protect the team from overload and out-of-hours assignment.

Safe baseline

Use Hybrid, AI Decides First, Summary on Human Handoff, a modest history limit, and explicit tool approvals. Change one setting at a time and verify it with a test conversation.

Detailed Operating Playbook

Primary owner: Organization admin or AI owner.

Team workflow

  • Save and test the provider key.
  • Choose the response and transcription models.
  • Set conversation, usage, and timeout limits.
  • Select orchestration and handoff behavior, then test one setting change at a time.

Success signals

  • The connection test succeeds.
  • The selected model is shown in settings.
  • Usage limits are documented.
  • A test conversation follows the selected orchestration mode.

When to review or escalate

Review this workflow when channels, policies, or workload change. Escalate to a manager when numbers look inconsistent or the same issue repeats more than once in the same day.