Product context
Connect conversations to the user and the task being performed.
- Identity and role context
- Session boundaries
- Accessible chat states
Text conversations
Chat AI agent connected to useful actions.
Help users complete a task in a text conversation, using approved knowledge, product context and bounded business actions.
- Permitted actions
- Retrieve permitted sources, ask clarifying questions and prepare or execute explicitly allowed product actions.
- Human approval
- Confirm consequential changes in the interface and let the user review the actual action details before they are submitted.
- When work cannot continue
- Explain missing information, offer a supported next step and pass conversation context to a human when the task cannot be completed.
Workflow design
How the chat AI agent works
A reference workflow for the supported task. The specific tools, approval rules and operating limits are agreed during discovery.
- 01
Resolve intent and identity
Identify the signed-in user and task; clarify ambiguous requests before selecting an action.
Output
An authorized conversation context
- 02
Retrieve useful context
Fetch approved knowledge or account data and retain references needed to explain the response.
Output
Relevant context with source references
- 03
Propose or perform a step
Validate action arguments and obtain confirmation where required before calling the product API.
Output
An approved action with a system response
- 04
Respond and hand off
Report the actual result and retain a concise task summary for follow-up or human assistance.
Output
A clear response or contextual handoff
Controls across the workflow
- Enforce permissions outside the model
- Validate tool inputs and results
- Limit retries and retain task state
- Log decisions with agreed data retention
Decisions that shape the scope
- How much conversation is remembered?
- Keep only the session context needed for the task. Persistent memory requires explicit retention, correction and access rules.
- When does the agent ask a question?
- Ask when required action fields or user intent are unclear. Do not infer consequential choices just to shorten the conversation.
- How are answers distinguished from actions?
- Show whether the agent is explaining information, proposing a change or reporting a completed operation. Confirm completion from the API response.
Evidence before expansion
Define what better means.
These are proposed evaluation measures, not reported client results. Agree the baseline, sample and acceptance threshold before the pilot, then review the evidence with the workflow owner.
- Grounded response quality
- Review representative conversations for source support, relevant context, correct clarification and unsupported statements.
- Action completion
- Compare proposed and executed actions with expected product state, including failed calls and repeated user submissions.
- Conversation recovery
- Evaluate ambiguous requests, abandoned sessions and handoffs for retained context and a useful next step.
Before you commit
Is this the right engagement?
Help users complete a task in a text conversation, using approved knowledge, product context and bounded business actions. A first release should cover a named task with representative examples and an accountable owner.
- What we need from you
- Bring representative conversations, product identities and roles, knowledge sources, action APIs, channel requirements and a human handoff route.
- How you accept the work
- Agree representative cases, failure scenarios and acceptance thresholds with the workflow owner. Review grounded response quality, action completion, conversation recovery before expanding access or supported tasks.
- Scope & alternatives
- This page covers the conversational agent inside a product or text channel. Customer support operations and organization-wide knowledge management are separate solution scopes.
Capabilities
What goes into your chat AI agent
Implementation components are selected for the task and confirmed in scope.
Knowledge and actions
Keep retrieved evidence and tool execution visible in the task flow.
- Permission-aware retrieval
- Action previews
- Result confirmation
Conversation operations
Review failures without treating conversation volume as evidence of value.
- Handoff summaries
- Feedback and trace review
- Versioned behavior changes
Frequently asked questions
Chat AI agent questions
01How is a custom chat AI agent different from a basic website chatbot?
How is a custom chat AI agent different from a basic website chatbot?
A production chat agent can be grounded in approved knowledge, preserve user permissions, use business tools, maintain workflow state, and escalate to humans. A basic chatbot often answers from a fixed script or isolated knowledge base.
02Can the chat agent use our internal knowledge?
Can the chat agent use our internal knowledge?
Yes. We can connect approved documents, knowledge bases, or data sources through retrieval with source lifecycle, permissions, indexing, and evaluation designed for the environment.
03Can it take actions in our systems?
Can it take actions in our systems?
Yes, but actions should be explicitly bounded. The agent can call approved APIs or tools with validation, permissions, confirmation, and human approval where the consequence requires it.
04Can it work inside our existing product?
Can it work inside our existing product?
Yes. We can embed it in web or application interfaces and connect it to the product's identity, account context, permissions, APIs, and analytics.
05How do you handle questions the agent cannot answer?
How do you handle questions the agent cannot answer?
We design clarification, safe refusal, fallback information, and human handoff. The agent should not invent answers merely to keep a conversation going.
06How do you improve a chat agent after launch?
How do you improve a chat agent after launch?
We review evaluation results, failed or escalated conversations, retrieval quality, tool errors, user feedback, and changing knowledge, then update the system through versioned releases.
Related
Connected services and workflows
Start a conversation
Scope your chat AI agent
Share the task, systems and examples of a successful result. We can define the first workflow, required controls and evaluation plan.