Scenario A
“I want to book an appointment tomorrow.”
Recognise the appointment request and start the appropriate workflow.
From requirement to production
OniLeo provides a structured path from a business requirement to a tested, published and continuously improved enterprise AI agent. Start with what the business needs the agent to accomplish, not with prompts, models or a blank workflow canvas.
DESCRIBE
BLUEPRINT
GENERATE
REFINE
CONNECT
TEST
PUBLISH
IMPROVE
01 · Describe
Describe the business requirement in natural business language. Focus on what customers need to accomplish, what information the agent may need, what questions it should answer, and when business actions or human assistance may be required.
Create a clinic assistant that can answer clinic questions, book or reschedule appointments, cancel bookings and transfer customers when human assistance is required.
Start in business language, not prompts, nodes or model configuration.
Business Goal
Customer Journeys
Operational Requirements
OniLeo Analysis
02 · Blueprint
OniLeo translates the requirement into a structured design for the agent. The Blueprint identifies what the agent needs to understand, what customer journeys it must support, what information and knowledge are required, and where decisions, actions or handoffs are needed.
The business outcomes the agent must support.
The customer needs and requests associated with those capabilities.
The information required to complete structured customer journeys.
The approved business information the agent needs to answer relevant questions.
The business journeys required for each capability.
Points where the journey must branch based on customer or business conditions.
External operations required to complete a process.
Situations where human assistance is required.
Example blueprint capabilities
03 · Generate
OniLeo uses the Agent Blueprint to generate the workflows required for each capability. Generated workflows can include information capture, decision points, enterprise knowledge steps, business actions, messages and human handoffs.
THE BLUEPRINT GENERATES THE WORKFLOWS.
Example 1 · Book Appointment
Example 2 · Clinic Information
04 · Refine
Generation accelerates the starting point and enterprise review provides control. Teams can inspect the generated workflows and refine information requirements, decision paths, messages, knowledge mappings, actions and handoffs before the agent is approved for testing.
05 · Connect
Add the approved enterprise information identified by the Blueprint and connect configured business actions required by the customer journeys. This gives the agent both the context to answer and the ability to participate in structured business processes.
Enterprise Knowledge
OniLeo Agent
Business Actions
Active journey: booking an appointment. The customer asks “What time does the clinic close?” The agent answers from approved enterprise knowledge, then continues the appointment journey.
Knowledge can support the conversation without discarding the active customer journey.
06 · Test
Before publishing, validate how the agent responds to expected journeys, variations, interruptions, missing information, knowledge questions and supported language changes.
Scenario A
“I want to book an appointment tomorrow.”
Recognise the appointment request and start the appropriate workflow.
Scenario B
“I do not have my patient ID.”
Handle unavailable information according to the configured workflow.
Scenario C
“Before that, what time does the clinic close?”
Answer from approved enterprise knowledge without losing the active journey.
Scenario D
“Can we continue in Hindi?”
Adapt the conversation language while preserving relevant context.
07 · Publish
Once the agent version has been reviewed and validated, publish the approved version to the required customer channels while keeping work-in-progress configuration separate from the live experience.
One approved agent configuration across the channels selected for the business use case. Working Version is never the same as Published Version.
08 · Improve
After publishing, operational signals help teams identify weak scenarios, knowledge gaps, workflow issues, handoff patterns and runtime behaviour that may require refinement. Changes can then be reviewed, retested and published as the next agent version.