What is PromptQL
PromptQL is a multiplayer AI agent designed for teams. It provides shared threads and a shared brain, allowing team members to collaborate with AI in a unified workspace. It automatically organizes context generated from team interactions into a knowledge base, turning it into suggested edits for a wiki. This wiki spans skills, knowledge, and the semantic layer, and users can accept these suggestions to continuously improve the system.
How to use PromptQL
- Start a shared thread: Work with your team in shared AI threads, similar to using Claude or ChatGPT but with multiplayer capabilities.
- Point it at your context: Connect PromptQL to your existing data sources like Slack, docs, tickets, CRM, and warehouse tables.
- Correct it once: When the AI makes a mistake, correct it. This correction becomes shared context that sticks for everyone.
- Accept suggested edits: PromptQL turns the context you generate into suggested edits for your wiki. Review and accept these edits to build your team's knowledge base.
- Use the wiki: The wiki contains interconnected pages that span skills, knowledge, and the semantic layer, making it easy to find and reuse information.
Features of PromptQL
- Multiplayer AI: Shared threads and a shared brain for team collaboration.
- Automatic knowledge base: Context is automatically organized into a wiki with suggested edits.
- Learning by correction: Correct the AI once, and it learns for everyone.
- Integration with existing tools: Works with Slack, docs, tickets, CRM, and warehouse tables.
- Transparency: Shows its work, including sources and assumptions.
- Reusable skills: Corrections become reusable skills (e.g., "exclude test accounts from revenue").
- Semantic layer: Changes to the semantic model are suggested and can be accepted.
- Cross-platform: Available on Mac, Windows, iOS, and Android.
Use Cases of PromptQL
- Customer Success: Analyze usage data and support tickets to identify churn risks, with context from team members.
- Support: Quickly resolve recurring issues by leveraging shared knowledge and tagging experts.
- Data Analysis: Use AI to analyze data from multiple sources and provide insights with cited sources.
- Team Knowledge Management: Automatically build and maintain a wiki from real work, reducing the need for manual documentation.
FAQ
Q: How does PromptQL learn?
A: PromptQL learns by being corrected. When you correct it, that correction becomes shared context that is used in future tasks.
Q: What data sources can PromptQL connect to?
A: It can connect to Slack, docs, tickets, CRM, and warehouse tables.
Q: Is PromptQL available on mobile?
A: Yes, it is available on iOS and Android.
Q: Can I try PromptQL?
A: Yes, you can get started by signing in or booking a demo.
