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PromptQL

PromptQL

Team AI coworker for querying business data, docs, context, and workflows.

PromptQL screenshot

What is PromptQL?

⚡ Quick Summary / TL;DR

PromptQL is an AI-driven AI Agents platform designed to team ai coworker for querying business data, docs, context, and workflows.. It is specifically optimized for Developer, Founder, Marketer seeking to streamline their workflow and enhance productivity.

Overview of PromptQL

PromptQL is a team AI coworker from Hasura for asking business questions across connected data, documents, and shared context. It helps teams plug in data sources, build a shared context wiki, and use the AI through the PromptQL app, desktop clients, mobile apps, Slack, Microsoft Teams, or embedded surfaces. The product is built for teams that want an AI agent to reason over company data instead of answering from a generic chat window. PromptQL provides infrastructure for secure code execution in the cloud, data connectors, authorization, project-level context, shared threads, and model choice across proprietary and open-weight models. PromptQL uses usage-based pricing around OLU, or Operational Language Unit, which normalizes token usage across models and token types. The pricing page lists an introductory $0.14 per OLU rate, a standard $0.20 per OLU rate, free credits for new projects, and enterprise options for larger teams. For FutureStack, PromptQL belongs in AI Agents because it turns business data and team context into a collaborative AI system. It is best for analytics, operations, product, finance, and data teams that want AI answers with connected sources, shared context, and governed access.

Best for

Business data agents, shared context, data questions, Slack agents, and team wikis.

Key Features of PromptQL

  • Multiplayer AI coworker for teams and shared context
  • Connects data sources, documents, and authorization rules
  • Works through app, desktop, mobile, Slack, and Microsoft Teams
  • Usage-based OLU pricing with model choice and free credits

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Pricing summary

PromptQL uses usage-based OLU pricing. The pricing page lists an introductory $0.14 per OLU rate, standard $0.20 per OLU pricing, up to $100 in free project credits, and up to $70 more per teammate.

Pricing & Plans for PromptQL

Free Credits

Start with project-level free credits and no card requirement.

Free
  • Up to $100 free credits
  • Up to $70 per teammate
  • No credit card to start
  • Project-level credits
Popular

Pay As You Go

Use PromptQL with OLU-based usage pricing.

Custom
  • $0.14 intro per OLU
  • $0.20 standard per OLU
  • No minimums
  • Auto-pauses at zero

Enterprise

Custom deployment and controls for larger organizations.

Custom
  • Custom terms
  • Governed data access
  • Team deployment
  • Enterprise support

Other pricing notes

  • Pricing checked on 2026-07-24 from PromptQL official pricing.
  • OLU means Operational Language Unit and normalizes token usage across models and token types.
  • Actual cost depends on query complexity, model choice, and team usage.
Pricing last checked: July 2026Official pricing page

Pros & Cons of PromptQL

Pros

  • Strong fit for teams asking questions across business data
  • Shared context wiki helps reduce repeated explanations
  • Works across app, desktop, mobile, Slack, and Teams
  • Usage pricing avoids fixed per-seat lock-in upfront
  • Built by Hasura, which gives it data-platform credibility

Cons

  • OLU pricing can be hard to forecast at first
  • Requires connecting data sources and authorization rules
  • Best value appears for teams, not solo casual users
  • Enterprise governance setup may take planning
  • Model choice can change usage and effective cost

Frequently Asked Questions about PromptQL

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