An AI operating system that syncs knowledge, skills, and capabilities across your team.
Free plan available, paid tiers aboveVisit WebsiteFreemiumVisit Website
Tracked since2026
The Bottom Line
- Price
- Free plan available, paid tiers above. Compare plans
Key facts
- Standardizes and scales AI workflows across teams.
- Centralizes AI knowledge, skills, and application deployment.
- Integrates with Claude Code or Codex to enhance team productivity.
Pros
- Ensures consistent AI usage and outputs across the organization.
- Accelerates team onboarding by providing a full AI playbook.
- Centralizes sensitive information like API keys securely.
- Promotes knowledge sharing and scalability of AI breakthroughs.
Cons
- Requires integration with existing LLM platforms like Claude Code or Codex.
- May have a learning curve for initial setup and management.
- Pricing model is not transparently listed as free or freemium.
What is Indigo?
HQ by Indigo AI is an AI operating system designed to standardize and scale AI workflows across an entire company. It acts as a shared context layer on top of large language models like Claude Code or Codex, enabling teams to transform individual AI breakthroughs into collective capabilities. The platform addresses the challenge of disparate AI tool usage and inconsistent prompt engineering by centralizing workflows, knowledge, and outputs.
HQ provides infrastructure for team synchronization, access control, secrets management, and application deployment. It allows companies to manage AI workers, knowledge bases, and project scaffolding, ensuring that best practices and successful AI applications are shared and adopted company-wide. This system aims to streamline onboarding, improve efficiency, and accelerate the adoption of AI-driven processes by making advanced AI capabilities accessible and consistent for all team members.
Available on: Web, macOS, Windows, Linux
Key Features
- Team Sync for skills, knowledge, and workflows
- Access Control for files and credentials
- Secrets Management for API keys and tokens
- One-command app deployment
- Desktop installer + AppBar app for management
- S3-backed, real-time file watching for synchronization
- Open-source AI dev team with 45 AI workers and 60+ skills
Pricing Plans
Pricing checked Sep 19, 2026
| Plan | Price | Details |
|---|---|---|
| Open Source Infrastructure | Free | |
| Indigo Build | Contact us |
Is Indigo worth the price?
Weak value
While the 'Open Source Infrastructure' is free, the 'Indigo Build' tier requires contacting sales, which often indicates a higher price point.
This structure is best for organizations with complex AI needs and a budget for custom solutions.
Reviews
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Indigo FAQ
How does Indigo facilitate consistent AI usage across an organization?
Indigo standardizes AI workflows and centralizes prompt engineering, ensuring consistent AI usage and outputs across the entire company. It transforms individual AI breakthroughs into collective capabilities by providing a shared context layer on top of large language models.
Which teams benefit most from using Indigo?
Teams looking to scale AI workflows, standardize AI tool usage, and improve efficiency through shared AI knowledge will find Indigo most beneficial. It is designed for companies aiming to accelerate the adoption of AI-driven processes and streamline onboarding for new team members.
How does Indigo compare to Notion for managing AI-related knowledge?
While Notion offers general knowledge management, Indigo specifically provides a centralized knowledge base tailored for AI workers and project scaffolding. Indigo focuses on standardizing and scaling AI workflows, whereas Notion is a broader workspace tool.
What kind of existing platforms does Indigo integrate with?
Indigo requires integration with existing large language model platforms to function, such as Claude Code or Codex. It acts as an operating system on top of these models to manage and scale AI workflows.
Does Indigo include a free tier for users?
Yes, Indigo is available on a free tier, allowing users to get started with its core functionalities. Paid plans are also offered for those requiring more extensive usage and additional features.
What are the main limitations of implementing Indigo?
A primary limitation is that Indigo requires integration with existing LLM platforms like Claude Code or Codex. There may also be a learning curve involved for the initial setup and ongoing management of the system.
How does Indigo secure sensitive information like API keys?
Indigo includes robust infrastructure for secrets management, centralizing sensitive information such as API keys securely. This ensures that critical credentials are protected while still being accessible for authorized AI applications.
Source: getindigo.ai