Onboarding a New Project
Onboarding provisions everything a new project needs to run the Q-AI Bot in one guided step: you fill in a short form and the AI New Customer Onboarding workflow does the rest.
What onboarding sets up
A single run creates:
| Created | What it is |
|---|---|
| A new knowledge store | The project's private knowledge base that the AI searches at answer time. It starts empty and fills as knowledge is added. |
| The project configuration | The project's row in the managed configuration database, linking its credentials, settings, and knowledge store together. |
| The Drive folder tree | A per-project root folder with knowledge-base, reports, and instructions subfolders, so files have a home from day one. |
| A cloned default prompt | A copy of the Generic System Prompt document, with the business name and phone filled in, ready to edit. |
| A cloned evaluation report | A copy of the Generic Response Evaluation Report sheet, used later to review answer quality. |
| Scenario import | The Q-AI scenarios that drive the conversation lifecycle are imported into the project's Texter environment. |
What you provide
You supply a small set of details. Have these ready before you start:
- Project id: the project's identifier in Texter.
- Business name and phone: used to personalize the cloned system prompt and the evaluation report.
- An admin email: the project owner is given access to the new Drive folder so they can manage their own knowledge files.
- Initial knowledge files: the first documents that describe the business (FAQs, price lists, service descriptions, and so on). These seed the project's knowledge base.
Onboarding gives the project sensible defaults. Fine-tuning (the prompt wording, the response behavior, and per-project options) happens afterward. See Per-Project Settings to adjust the configuration, and the Knowledge Base pages to add more material later.
Run it and test
Run onboarding once per project from the Onboard AI Bot tool. Each run creates fresh resources, so use the knowledge-base and settings flows for later changes. To verify, confirm the Q-AI scenarios imported (search q-ai in the Scenario Marketplace) and run an end-to-end check with the AI Bot recipe.
Related pages
- Q-AI Bot Overview: how the system fits together.
- Per-Project Settings: tune the configuration after onboarding.
- Knowledge Base: add and maintain the project's knowledge.
- Conversation Lifecycle: what the imported scenarios actually do.