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Daemons
Quiet
#2732 Radar 50

Always-on AI processes that proactively maintain codebases and workflows.

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Product memo

Daemons gives engineering teams always-on AI processes that proactively maintain code quality, documentation, and workflows. Operating across GitHub, Linear, and Slack, it uses simple Markdown files to define roles and expected outcomes. This frees developers to focus on novel work, as Daemons handle recurring maintenance and follow-through, building trust through compounding memory and predictable behavior.

For who

Engineering teams and developers

Solves what

Proactive, always-on AI processes that maintain codebases and workflows.

  • Always-on AI processes
  • Defined by Markdown files
  • Compounding org-wide memory

In their own words

Daemons work 24/7. No prompts required.

Daemons are always-on AI processes that work proactively across Slack, Linear, GitHub, and more. Defined with simple .md files, daemons work 24/7 without explicit instruction so your team can focus on novel work.

CTA: [Try daemons now]

Commercial cues

Pricing snapshot usage based with free tier

Model

usage based

Free tier

Yes

Trial

Available

No public pricing tiers captured.

Pricing Strategy

Key Tactics
  • A free tier removes friction for initial adoption and low-volume use.
  • Usage-based overage credits allow flexible scaling of AI process throughput.

Operator context

Operating setup

Founded

Jun 2026

Platform

API

Audience

Developers

Market demand

Daemons keyword demand

5 keywords

5 keywords
Upgrade to Starter

Market demand is Starter-tier market intelligence.

Derived from this product’s latest SimilarWeb keyword mix — directional demand, not proof.

Builder Strategy

Strategy Type
Niche Specialist
Stage
Vc Growth
Effort
Small Team
About Daemons Expand

Daemons provides engineering teams with always-on AI processes designed to proactively maintain codebases and workflows. It helps developers offload recurring maintenance tasks, allowing them to concentrate on new development.

The system operates across platforms like GitHub, Linear, and Slack, with daemon roles and outcomes defined through simple Markdown files. This approach builds compounding organizational memory and ensures predictable behavior, establishing a unique positioning in the AI automation market by focusing on continuous, unprompted work rather than reactive task execution.