About Obi
Obi, developed by Cor (Corellian Systems), is a voice AI agent designed for customer onboarding and user activation. It functions like a live video call, using voice and on-screen awareness to guide users through product setups, share best practices, and answer questions in real time. Obi aims to replace static tooltips, videos, and manual walkthroughs with a conversational, 24/7 interactive experience that scales with the business. It learns from existing training materials and provides detailed insights into user sessions to help teams identify and fix onboarding friction.
How to Use
To use Obi, first provide the AI with your existing training videos or documentation. It uses an AI Training Mode to learn your product in minutes. After reviewing the training, you can deploy Obi by sharing a link, adding it to your onboarding academy, or embedding it directly into your product using a JavaScript snippet. You can then monitor session reports to optimize the user experience.
Key Features
- Voice and on-screen awareness for real-time guidance
- Automated training from existing videos and docs
- 24/7 availability in multiple languages
- Segment-based experience tailoring
- In-app integration via JavaScript snippet or SDK
- Session analytics and drop-off tracking
- Human-like conversational interaction
Use Cases
- Scaling SME onboarding from manual calls to AI-led sessions
- Training users on highly technical software without human intervention
- Reducing support tickets by answering setup questions in real-time
- Improving user activation through personalized, interactive walkthroughs
Key Features
Pros & Cons
- Highly interactive and personalized user experience
- Available 24/7 without human intervention
- Scales infinitely with business growth
- Reduces reliance on support tickets and static content
- Provides actionable insights for product improvement
- Quickly trainable from existing materials
- Requires paid subscription, no free tier mentioned
- Integration needed for on-screen awareness in products
- Potential privacy concerns with screen monitoring
- Effectiveness depends on voice clarity and accents
- Limited to voice and screen-based interactions
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