About This Site
Collaborative AI workspace with shared team context and an automatically maintained knowledge base PromptQL is a multiplayer AI platform for teams that combines shared AI threads, connected business data, collaborative corrections, and a self-organizing team wiki. It works like Claude or ChatGPT with shared context, allowing teammates to review answers, tag experts, preserve reasoning, and turn corrections into reusable skills and knowledge. PromptQL connects sources such as Slack, documents, CRM systems, SaaS applications, data warehouses, coding agents, and product analytics while providing scoped permissions and audit controls.
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Key Features AI
Core Features
Multiplayer AI threads with shared team context
Collaborative answer review, correction, and refinement
Automatically suggested wiki and knowledge-base updates
Connections to Slack, Google Docs, CRM systems, SaaS applications, data warehouses, and analytics tools
Source citations, visible assumptions, and step-by-step work
Reusable team skills and semantic-layer knowledge
Wikipedia-like pages with revision history and editorial controls
Scoped access controls and granular multi-user permissions
Data-access audit trails
External, confidential, and personal context separation
Per-thread model selection across proprietary and open-weight models
OLU-based usage tracking with per-step consumption details
Per-user quotas, spending alerts, prepaid billing, and auto-pause controls
Enterprise security features including SSO, private networking, dedicated VPC, and BYOC
Advantages
Preserves team reasoning and corrections instead of isolating knowledge in private AI chats
Connects multiple business systems and data sources in one AI workspace
Automatically turns validated corrections into reusable shared context
Shows sources, assumptions, and detailed OLU usage for greater transparency
Supports granular scopes and permissions for internal, external, confidential, and personal use cases
Offers many model choices, including lower-cost open-weight models
No per-seat license or minimum usage requirement on the Starter plan
Provides free project credits and additional credits when teammates join
Enterprise plans include advanced security, SSO, audit trails, private networking, and dedicated infrastructure
缺点：Usage costs vary with task complexity, model selection, and OLU consumption
缺点：The pricing model may be harder to estimate than a fixed monthly subscription
缺点：Enterprise features require contacting sales for custom pricing
缺点：Free credits apply to the first created project and are limited
缺点：Accuracy still depends on human review and the quality of connected data
缺点：Some advanced AI models consume substantially more OLUs than open-weight alternatives
缺点：Connecting sensitive company systems requires careful configuration of scopes and permissions
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30-Day Click Trend
08-22
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