⚖️Side-by-Side Comparison

OpenHistory vs Hellomatik: Which is Better in 2026?

We've compared 2 tools across pricing, features, ratings, and reviews to help you make an informed decision. No paid placements — just facts.

Compare different tools →
Feature
OpenHistory logo
OpenHistory

Productivity & Automation

Hellomatik logo
Hellomatik

Productivity & Automation

RatingNo reviews yetNo reviews yet
PricingFree

as of Sep 30, 2026

Contact Sales

as of Sep 26, 2026

Pricing ModelFreeContact Sales
Free Plan
Free Trial
API Available
Verified
Founded——
HQ——
Team Size1-10—
Platforms——
Top Integrations——
Key Features
  • Permission-scoped activity capture
  • Hourly and daily summaries
  • Local AI agent access
  • No sensitive capture by design
  • No telemetry
  • Company blueprint
  • Human-in-the-loop approval
  • Sales & purchasing use cases
  • Logistics use cases
  • Custom use-case rollout
Description

OpenHistory is an open-source macOS app that builds a private, searchable timeline of a user's work by observing only the foreground activity they explicitly permit — window names, document context, browser domains, clicks, and visible interface text via macOS Accessibility APIs. It generates hourly and daily summaries and gives approved local AI agents a controlled way to answer questions about what the user did, using Apple's local Foundation Model by default or, optionally, OpenAI, Anthropic, or Kimi. By design, it does not capture screenshots, audio, camera or microphone input, passwords, private browser windows, or low-level keystrokes, and sends no analytics or telemetry of its own. All activity, timelines, summaries, settings, and agent connections are stored in a permission-restricted directory on the user's own Mac. It requires macOS 14 or later and is available on GitHub and via a direct download from its own site.

Hellomatik deploys AI agents that automate business operations using a company's own data, aimed at automating recurring operational workflows (not just answering questions) by grounding agent actions in the business's actual internal data. It is aimed at operations teams that want AI agents to actually execute recurring operational tasks using real company data, not a generic chatbot layered on top.