🗝️Triggering a Kaiya Mission

Learn how Kaiya triggers a Mission—from matching user queries to triggers, orchestrating AI agents, executing steps, and delivering structured insights.

Here, we break down the entire agentic Mission—from when a user types a query to when the Mission is executed and completed using AI agents in Tellius. It applies universally to all Agentic Missions regardless of use case (e.g., revenue analysis, product discontinuation, churn prediction etc.).

To trigger a user-defined Mission or let Kaiya plan and automate the analysis step by step, click the Deep Insight button.

1. User initiates query

When the user interacts with Kaiya by entering a natural language query in the chat interface, it is evaluated in real time against a list of triggers configured for published agentic flows.

Each Kaiya Mission contains one or more trigger phrases defined during Mission creation in Composer. These triggers allow Kaiya to intelligently map user input to the correct Mission, even if the phrasing is not exact. Trigger variations are supported, meaning you can ask a question in different ways, and Kaiya will still recognize the intent.

2. Kaiya maps query to a trigger

If a match is found, Kaiya responds with the name and description of the matching agentic Mission, and prompts user confirmation to initiate the Mission execution. This user confirmation ensures control and transparency before any backend processing begins.

Choose “Yes” to continue, else select “No” to abort the Mission exection.

Matching the trigger with the Mission

3. Mission initialization

Upon confirmation, Kaiya activates the Planner Agent. The Planner Agent's job is to:

• Interpret the Mission's objective

• Break it into logical, executable steps

• Identify which agents need to be involved

• Sequence these agents correctly

Supervision Agent working behind the scenes

The Planner Agent acts as the orchestrator or mission control of the entire agentic flow. It ensures the right agents are activated at the right time in the right order.

4. Squad of AI Agents

A message appears as follows: “Squad of AI Agents... Finding the best agent to execute next step.” This indicates that Kaiya is identifying and activating the most suitable agent for the task at hand. The agents activated depend entirely on the Mission steps defined in Composer. Agents begin executing each Mission step , using the logic defined in Composer. Commonly involved agents include:

Agent Name	Role
Validation Agent	Checks query structure, permissions, and data readiness
Planner Agent	Breaks down requests, assigns agent tasks, sequences execution
Data Prep Agent	Filters, joins, and loads relevant data from selected Business Views
Visualization Agent	Generates appropriate visuals (charts, tables, graphs)
Insights Agent	Performs root cause analysis, trend detection, and pattern mining
Summary Agent	Converts insights into plain-language narratives and summaries
Knowledge Graph Agent	Maps relationships, finds entity connections, powers recommendations

Each of these agents has a specific, modular purpose, and they are invoked only if required by the defined step logic.

Analytic Agent working behind the scenes

Conditional logic and dependencies between steps are respected. Prompts for additional user input (e.g., filters, time periods, dimensions) may be triggered dynamically. This modular structure enables Kaiya to adapt Missions based on data state, user interaction, or complexity of analysis.

7. Result generation

Once the Kaiya Mission completes execution, visuals, summaries, and insights are presented back to the user. Responses appear conversational but are powered by structured backend analysis.

• Charts and graphs (auto-generated)

• Tabular data

• Root cause explanations

• Text summaries with recommendations

• Drill-down links or options

Result generation

8. Post-execution actions

• Ask follow-up questions to go deeper

• Share results or trigger a different Mission

• Request variations or filtered views of the current output

Post-execution actions