Comparison
future-agi vs kitaru
Verdict
Pick future-agi if future-AGI is an open-source platform for evaluating and observing LLM and AI agent applications, offering features like tracing, evaluations, simulations, and guardrails. It is self-hostable and supports deployment via,; pick kitaru if kitaru focuses on recording, replaying, and enhancing the performance of AI agents in production environments using technology from ZenML.
Markdown twin · future-agi alternatives · kitaru alternatives
GraphCanon updated Sep 29, 2026
7views this month
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Trust & integrity
| Signal | future-agi | kitaru |
|---|---|---|
| Maintenance | Very active (0d since push) As of Sep 18, 2026 · github_public_v1 | Very active (0d since push) As of Sep 29, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 18, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 29, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Sep 18, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- future-agi
- Open-source, end-to-end platform for evaluating, observing, and improving LLM and AI agent applications
- kitaru
- Record, replay, and improve AI agents in production, built on ZenML
Stars
- future-agi
- 2.0k
- kitaru
- 297
Forks
- future-agi
- 627
- kitaru
- 25
Open issues
- future-agi
- 961
- kitaru
- 48
Language
- future-agi
- Python
- kitaru
- Python
Adopt for
- future-agi
- Future-AGI is an open-source platform for evaluating and observing LLM and AI agent applications, offering features like tracing, evaluations, simulations, and guardrails. It is self-hostable and supports deployment via,
- kitaru
- Kitaru focuses on recording, replaying, and enhancing the performance of AI agents in production environments using technology from ZenML.
Persona
- future-agi
- -
- kitaru
- -
Runtime
- future-agi
- -
- kitaru
- -
License
- future-agi
- Apache License 2.0, allowing for free use, modification, and distribution of the software, with the condition that any derivative works also be licensed under the same terms.
- kitaru
- Apache-2.0
Last pushed
- future-agi
- Sep 18, 2026
- kitaru
- Sep 29, 2026
Categories
- future-agi
- AI Agents, Evaluation & Observability, LLM Frameworks
- kitaru
- AI Agents, Evaluation & Observability
Trust and health
Open issues (now)
- future-agi
- 961
- kitaru
- 48
Stars delta
- future-agi
- +473 (30d)
- kitaru
- +71 (30d)
Open issues delta
- future-agi
- +365 (30d)
- kitaru
- -1 (30d)
Full report
- future-agi
- Trust report
- kitaru
- Trust report
Choose future-agi if…
- Pricing: The core platform is free and open-source under the Apache License 2.0. However, for managed services or additional support, contact sales for pricing..
- Requirements: Min 4 GB RAM; Requires Docker; Future-AGI requires Docker for deployment, with support for Docker Compose and upcoming Kubernetes and Helm support.; For production environments, a setup script is provided to generate secrets and pin image tags, ensuring a secure and reproducible deployment..
- Tags unique to future-agi: ai-evals, ai-gateway, ai-optimization, ai-simulations.
- Also covers LLM Frameworks.
- You need a self-hostable solution that does not phone home, ensuring full control over your data and evaluation logic.
When NOT to use future-agi
- You require immediate Kubernetes or Helm support, as these are not yet available, though they are in development.
- You are seeking a managed service or a solution available through AWS Marketplace, as these options are not yet available, though they are planned for the future.
- Your project is in a highly dynamic environment where frequent updates and vendor support are critical, as Future-AGI is a community-driven project with a focus on self-hosting and open-source.
Choose kitaru if…
- Tags unique to kitaru: agent-framework, checkpoints, durable-execution, llm.
- - You need to ensure the continuous improvement of AI agents that are already deployed; Kitaru allows you to replay scenarios with different approaches to identify improvements.
- More recently updated (last pushed Sep 29, 2026).
When NOT to use kitaru
- - If your project is in the early stages of development without a clear need for replaying historical data or improving upon past behaviors;
- - When working outside Python, as Kitaru does not currently offer support for other programming languages.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (future-agi/future-agi) · observed Sep 20, 2026
- GitHub forks (future-agi/future-agi) · observed Sep 20, 2026
- Last push (future-agi/future-agi) · observed Sep 18, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
- GitHub stars (zenml-io/kitaru) · observed Sep 29, 2026
- GitHub forks (zenml-io/kitaru) · observed Sep 29, 2026
- Last push (zenml-io/kitaru) · observed Sep 29, 2026
- License file (Apache-2.0) · observed Sep 29, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: future-agi 2.0k · kitaru 297 (synced Sep 20, 2026).
Common questions
- What is the difference between future-agi and kitaru?
- future-agi: Open-source, end-to-end platform for evaluating, observing, and improving LLM and AI agent applications. kitaru: Record, replay, and improve AI agents in production, built on ZenML. See the comparison table for live GitHub stats and shared categories.
- When should I choose future-agi over kitaru?
- Choose future-agi over kitaru when Pricing: The core platform is free and open-source under the Apache License 2.0. However, for managed services or additional support, contact sales for pricing.; Requirements: Min 4 GB RAM; Requires Docker; Future-AGI requires Docker for deployment, with support for Docker Compose and upcoming Kubernetes and Helm support.; For production environments, a setup script is provided to generate secrets and pin image tags, ensuring a secure and reproducible deployment.; Tags unique to future-agi: ai-evals, ai-gateway, ai-optimization, ai-simulations; Also covers LLM Frameworks; You need a self-hostable solution that does not phone home, ensuring full control over your data and evaluation logic.
- When should I choose kitaru over future-agi?
- Choose kitaru over future-agi when Tags unique to kitaru: agent-framework, checkpoints, durable-execution, llm; - You need to ensure the continuous improvement of AI agents that are already deployed; Kitaru allows you to replay scenarios with different approaches to identify improvements; More recently updated (last pushed Sep 29, 2026).
- When should I avoid future-agi?
- You require immediate Kubernetes or Helm support, as these are not yet available, though they are in development. You are seeking a managed service or a solution available through AWS Marketplace, as these options are not yet available, though they are planned for the future. Your project is in a highly dynamic environment where frequent updates and vendor support are critical, as Future-AGI is a community-driven project with a focus on self-hosting and open-source.
- When should I avoid kitaru?
- - If your project is in the early stages of development without a clear need for replaying historical data or improving upon past behaviors; - When working outside Python, as Kitaru does not currently offer support for other programming languages.
- Is future-agi or kitaru more popular on GitHub?
- future-agi has more GitHub stars (2,032 vs 297). Stars measure visibility, not whether either tool fits your constraints.
- Are future-agi and kitaru open source?
- Yes - both are open-source projects on GitHub (future-agi: Apache-2.0, kitaru: Apache-2.0).
- Where can I find alternatives to future-agi or kitaru?
- GraphCanon lists graph-backed alternatives at future-agi alternatives and kitaru alternatives (future-agi markdown twin, kitaru markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, future-agi or kitaru?
- future-agi: Very active. kitaru: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
- Where are the full trust reports for future-agi and kitaru?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: future-agi trust report; kitaru trust report.