What is Hyper?
Hyper is a background intelligence system that automatically gathers context from your team's existing tools: email, documents, Slack, code repositories, CRM systems, and meeting recordings, then centralises this knowledge in a shared brain. This context flows directly into the AI assistants you already use, including Claude, Cursor, ChatGPT, and Codex, without requiring setup or prompts.
The tool targets teams that want their AI tools to understand company-specific information, decisions, and history without constant reconfiguration. It operates silently in the background, continuously updating as your team collaborates.
What sets Hyper apart is its focus on augmenting your existing AI tools rather than replacing them. It treats your company's collective knowledge as a first-class resource accessible across your entire AI toolkit.
Key Features
Automatic context synchronisation from email, Slack, documents, code, CRM, and meeting recordings
Integration with multiple AI platforms including Claude, Cursor, ChatGPT, and Codex
Background processing that operates without manual intervention or configuration
Centralised knowledge base built from dispersed team communication and tools
Real-time updates as team members create and share content
Pros & Cons
Advantages
- Augments AI tools you already use; no need to switch platforms
- Automatic context gathering eliminates repetitive manual prompting
- Prevents information silos by centralising knowledge across tools
- Supports multiple AI platforms simultaneously from one knowledge base
- Requires minimal setup and ongoing maintenance
Limitations
- Requires integrations with multiple third-party tools to be fully effective
- Privacy and data security considerations when aggregating company information
- Effectiveness depends on your team actively using integrated tools
- May require time to understand what context is being prioritised
- Potential cost scaling as team size and data volume increase
Use Cases
Customer success teams using AI to draft responses with full customer history and context
Engineering teams using AI code assistants with repository and documentation context
Product teams using AI writing tools with access to customer feedback and roadmap information
Sales teams using AI with CRM data and email history for prospect research and outreach
Onboarding new team members with AI agents that have context about company processes and decisions