Adaptation bot

Technical task for the development of an assistant bot for managing the adaptation process of new employees

1. Project description

It is necessary to develop an assistant bot that will work with a knowledge base and help in the adaptation of new employees, as well as automate their training process. The knowledge base is formed by the administrator and used by the bot to generate training content, tests, and exam tasks.

2. User roles

2.1. Administrator

The administrator has the following functions:

 • Checking the exam results of the new employee.

 • Checking and changing the status of the interview.

 • Managing job vacancies (adding/deleting/updating).

2.2. Recruiter

The recruiter performs the following actions:

 • Adds information about new candidates.

 • Changes the status of the interview.

2.3. New employee

The new employee goes through the adaptation process, which includes:

 1. Filling out a questionnaire and specifying the position.

 2. Receiving an individual training plan for 7 days.

 3. Taking daily tests.

 4. Final exam on the 7th day, the results of which are sent to the administrators.

 5. Questions in tests and exams are generated by the bot from the knowledge base according to the position.

3. Functional requirements

3.1. Assistant bot

The bot must:

 • Automatically generate a training plan for the new employee for 7 days.

 • Create tests at the end of each day based on the knowledge base.

 • Conduct a final exam on the 7th day.

 • Send test and exam results to the administrators.

 • Interact with users through a convenient interface (Telegram, Slack, web platform, etc.).

3.2. Working with the knowledge base

 • The administrator forms the knowledge base, adds and edits data.

 • The bot uses the knowledge base to generate training content, tests, and exams.

3.3. Managing the hiring process

 • The recruiter adds candidates and changes their interview status.

 • The administrator controls the process and can change the status.

 • The bot stores all information about candidates and their statuses.

4. Technical requirements

4.1. Development environment

 • Programming language: Python (or Node.js, if more suitable).

 • Chatbot framework: Telegram Bot API / Dialogflow / Rasa / BotPress.

 • Database: PostgreSQL / Firebase / MongoDB.

4.2. APIs and integrations

 • Telegram API (if the bot will work in Telegram).

 • Google Sheets API (for data storage, if needed).

 • Webhook for sending notifications.

4.3. Architecture

 • Microservices or server architecture.

 • Scalability capability.

 • Logging and monitoring of the bot's operation.

5. Interfaces

1. Chatbot: The main interface for user interaction.

2. Administrator panel: Web interface or Telegram commands for managing processes.

6. Work scenarios

6.1. New employee registration scenario

 1. The new employee launches the bot and fills out the questionnaire.

 2. The bot forms an individual training plan.

 3. Over 7 days, the employee undergoes training and testing.

 4. On the 7th day, the final exam is conducted.

 5. The exam results are sent to the administrator.

6.2. Recruiter work scenario

 1. The recruiter adds a new candidate.

 2. Changes the status of the interview during the hiring process.

6.3. Administrator work scenario

 1. Checks the exam results.

 2. Changes the statuses of interviews.

 3. Manages job vacancies.

7. Security requirements

 • User authentication and authorization.

 • Data protection in the knowledge base.

 • Role-based access control (administrator, recruiter, employee).

8. Project development

 • Adding a mentoring module.

 • Integration with CRM systems.

 • Analytics and reports on employee adaptation.

9. Development timelines and stages

Stage 1. Analysis and design (1-2 weeks)

 • Defining the structure of the database.

 • Preparing API endpoints.

Stage 2. MVP development (4-6 weeks)

 • Developing the bot.

 • Implementing the knowledge base.

 • Testing interactions.

Stage 3. Testing and debugging (2-3 weeks)

 • Testing scenarios.

 • Performance optimization.

Stage 4. Deployment and support

 • Implementation in the working environment.

 • Collecting feedback and refinement.

10. Expected result

After the project implementation, the company will receive:

 • An automated employee adaptation system.