Tool Information
Passarel is an AI tool designed to streamline the onboarding process for new employees. By leveraging custom language models and domain-specific data, Passarel enables organizations to create personalized onboarding experiences for their hires. With Passarel, new employees always have access to an onboarding buddy, available round the clock.One of the key features of Passarel is its ability to integrate with existing documentation and knowledge bases, allowing organizations to build bespoke GPT (Generative Pre-trained Transformer)-like models for onboarding. This flexibility extends to selectively fine-tuning the integrations and material that constitute the unique AI model.Data security is a priority for Passarel. The tool does not retain any uploaded documents or data once the model is created. All processed information and uploaded documents are permanently erased from storage. This ensures the privacy and safety of sensitive company information.Once the AI model is developed, organizations can deploy it as a bot on popular chat platforms such as Slack, Microsoft Teams, or as an independent chatbox within their own dashboard. This deployment enables employees to access on-demand knowledge conveniently, directly from these platforms.Passarel aims to provide an effortless and effective onboarding experience for organizations by leveraging the power of AI and tailored language models. By automating the onboarding process, organizations can save time and ensure consistent and personalized support for new hires.
F.A.Q (20)
Passarel is an AI tool that streamlines the onboarding process for new employees. It creates a personalized onboarding experience by integrating with existing documentation and chat platforms.
Passarel personalizes the onboarding process by using custom language models and domain-specific data. This enables organizations to create tailored onboarding experiences for their hires. Further personalization is achieved by integrating with existing documentation and knowledge bases.
Passarel uses AI by employing custom language models and domain-specific data for employee onboarding. This allows it to automate the process, making it more efficient and personalized. It can also be deployed as a bot on popular chat platforms for on-demand knowledge access.
The primary function of Passarel is to streamline and personalize the onboarding process for new employees by leveraging AI, domain-specific data and integrated documents.
Yes, Passarel can integrate with existing documentation. This allows organizations to build bespoke GPT-like models for onboarding and fine-tune the material that makes up the unique AI model.
A GPT-like model in Passarel refers to the Generative Pre-trained Transformer models it uses. These models leverage existing documentation and knowledge bases to create custom onboarding experiences.
Passarel can be deployed on popular chat platforms like Slack, Microsoft Teams. It can also be used as an independent chatbox within an organization's own dashboard.
Passarel uses company-specific data to create its models. It allows users to fine-tune these models further with integrated resources.
No, Passarel does not retain any of the uploaded data. After the AI model is created, all uploaded documents and processed information are permanently erased from storage.
Passarel ensures data security by not retaining any uploaded documents or data once the model is created. All uploaded documents and processed information are permanently erased from storage, ensuring the safety of sensitive company information.
Yes, Passarel can be used as an independent chatbox within an organization's own dashboard. This allows employees to access on-demand knowledge directly from the platform.
As an AI tool designed to automate and tailor the onboarding process, Passarel best suits organizations seeking to streamline their onboarding process and provide a personalized experience for new hires.
Users can fine-tune the integrations in Passarel by selectively adjusting the existing documentation and knowledge bases that constitute the unique AI model.
The onboarding buddy feature in Passarel refers to the AI model's capacity to be available round the clock, providing on-demand knowledge and support to new employees.
Passarel helps save time in the onboarding process by automating it. It uses tailored language models and AI to create a streamlined, personalized onboarding experience for new hires, reducing the manual effort required.
Passarel ensures the privacy of company information by not retaining any uploaded documents or data after the AI model is created. All processed information and uploaded documents are permanently erased from their storage.
Yes, with Passarel you can blend your existing knowledge base. It integrates with an organization's existing documentation and knowledge bases to build tailored GPT-like models for onboarding.
A custom language model in Passarel refers to the system's ability to use domain-specific data to create personalized onboarding experiences. These models are created using the existing company documentations and knowledge bases.
Passarel provides personalized support for new hires by creating a unique AI model for each onboarding process. This model uses domain-specific data and integrates with existing documentations, allowing an on-demand, 24/7 assistance for employees.
Automating the onboarding process with Passarel has a multitude of benefits. It saves time by reducing manual effort, provides a personalized experience for new hires through tailored models, ensures data security, and offers on-demand knowledge through deployment on popular chat platforms and within the organization's own dashboard.
Pros and Cons
Pros
- Personalizes onboarding
- Integrated docs and chat
- 24/7 onboarding buddy
- Custom language models
- Domain-specific data customization
- Secure data processing
- Erases data post-processing
- Available as chatbot
- Slack and Microsoft Teams compatible
- Can be independently integrated
- Automates onboarding process
- Saves time
- Provides consistency
- Highly flexible
- Company specific data tuning
- No storage of data
- On-demand knowledge availability
Cons
- Data purged after model creation
- Limited deployment options
- No standalone application
- Onboarding specific
- No data retention policy
- Latency on complex queries
- Requires extensive integrations
- No data review post-operation
- Not openly pricing
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