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Hindsight

Hindsight: Agent Memory That Learns

7.5 Open source61k
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Hindsight homepage
hindsight.vectorize.io · captured 2026-09-28

Our verdict

A usable project with some maintenance caveats. This assessment is derived from GitHub's own repository metrics on 2026-09-28, not from hands-on testing.

Hindsight: Agent Memory That Learns. The project is written primarily in Python, released under MIT, and has 59,797 stars and 7,342 forks on GitHub. 266 contributors have committed to it, and the most recent push was 2026-11-07. The latest tagged release is v1.2.0 (2026-11-03). Figures come from the GitHub API on 2026-11-08 and are refreshed weekly; the score below weighs adoption, maintenance, release discipline, contributor breadth, licence clarity and issue hygiene.

Reviewed by AI Review Rating from GitHub API data How we score

RepositoryGitHub API, refreshed weekly

61kStars
7.4kForks
115Watching
291Contributors
229Open issues
Licence
MIT
Language
Python
Last push
2026-11-14
View on GitHub

Releases

  1. v1.2.1 v1.2.1
  2. v1.2.0 v1.2.0
  3. v1.1.0 v1.1.0
  4. v1.0.0 v1.0.0
  5. v0.10.3 v0.10.3
  6. v0.10.2 v0.10.2

Pros and cons

Pros

Pricing

  • Free tierYes
  • LicenceMIT
  • Self-hostYes, source is public
  • Public price listNot published

Hindsight does not publish a web price list. For consumer apps that usually means pricing appears inside the product; for enterprise tools it means talking to sales. Why we do this

Visit hindsight.vectorize.io

Changelogwhat changed, most recent first

User reviews

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Hindsight alternatives

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Articles on Hindsight

Questions

Is hindsight free?

Yes. hindsight advertises a free tier on its own site.

How much does hindsight cost?

hindsight does not publish a web price list. For consumer apps that usually means pricing appears inside the product; for enterprise tools it means talking to sales.

Is hindsight open source?

Yes. hindsight is a public repository released under MIT. You can self-host or inspect the source directly.

How is hindsight scored here?

hindsight scores 7.5 out of 10. That comes from a desk review of public evidence, which is capped at 8.5 out of 10: public pricing, documentation, maintenance signals and how much we could actually verify. Affiliate relationships are excluded from scoring entirely. The full rubric is published on our methodology page.

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