Overview of Aisera Platform Administration

To create and develop your Aisera bot or application, access the Aisera Gen AI Platform using the Aisera Administration application - the interface that administrators use to create and configure the Aisera applications (bots). The is also known as the Aisera Admin UI.

End-to-End Bot Set up Steps

The Aisera Admin UI opens when you choose your Aisera tenant URL in a browser window.

The complete list of bot creation steps (with links to sections with steps) is:

  1. Get an Aisera tenant from your Aisera Team, and have the team set up a Customer Administrator account. Example tenant syntax: https://<tenant_id>.login.aisera.cloud

  2. Go to the customer's data system and create credentials so the Aisera Service User can log into it.

  3. Run a Data Ingestion job to bring the User, Ticket, File or Knowledge Base info to the Aisera platform.

  4. Choose a bot type from the left nav menu and build an Application/Bot.

  5. View the default Conversations for the Bot and modify as needed.

  6. Add a channel as the 'skin' for your bot/application.

  7. Create Workflows or Hyperflows for your bot.

  8. Get an Aisera Admin to add your Workflows to the Bot Advanced settings window.

  9. Test the workflow, modify, and repeat.

  10. Use the Intents window to modify flows and repeat.

  11. Train your bot by creating feedback and running it many times to teach it the correct responses. If you can create and run an automated script for this, it's best. This might have to be done by your Aisera Admin.

All steps except 1, 4, 13, 14, and 16 can be done in the Aisera Admin UI.

Included in this section

The following chapters in this section describe how to configure, train, and maintain Aisera applications with the administration interface (Aisera Admin UI).

Aisera Platform Configuration (Roles, Access, SSO, Logs)

Integrations and Data Sources (Generic Connector, Integrated Systems, Best Practices)

Channels (Aisera application skins, Integrated Channels)

Data Ingestion (Data Configuration, Ticket or KB Article Ingestion, Best Practices, Troubleshooting)

Post-Ingestion Tasks (System Jobs - Indexing and Extraction)

AI Automation (Workflows, Hyperflows, Event Studio, System Triggers)

Security & Privacy (TRAPS) (Masking PII, Managing Risks)

LLM Operations (Benchmarking, Prompts Studio, Gateway, Ontology)

Analytics (Pre-Built and Custom)

AI Workbench (Unresolved Request Data)

Content Generation (Requests and Tickets from Conversations)

Generative AI Learning (Ticket Learning, Knowledge Generation)

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