Comparison
headroom vs paig
Verdict
Pick headroom if headroom compresses data for LLMs, reducing token usage by 20% for coding agents and 60-95% for JSON, without altering answers. It offers a library, proxy, and MCP server; pick paig if pAIG is an open-source security tool for generative AI applications that focuses on compliance and guardrails.
Markdown twin · headroom alternatives · paig alternatives
GraphCanon updated Sep 20, 2026
Trust & integrity
| Signal | headroom | paig |
|---|---|---|
| Maintenance | Very active (0d since push) As of Sep 18, 2026 · github_public_v1 | Dormant (401d since push) As of Sep 11, 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 11, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Sep 20, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 15, 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
- headroom
- Compress tool outputs, logs, files, and RAG chunks before they reach the LLM.
- paig
- Protects Generative AI applications by ensuring security, safety, and observability
Stars
- headroom
- 73k
- paig
- 211
Forks
- headroom
- 5.6k
- paig
- 217
Open issues
- headroom
- 671
- paig
- 57
Language
- headroom
- Python
- paig
- CSS
Adopt for
- headroom
- Headroom compresses data for LLMs, reducing token usage by 20% for coding agents and 60-95% for JSON, without altering answers. It offers a library, proxy, and MCP server.
- paig
- PAIG is an open-source security tool for generative AI applications that focuses on compliance and guardrails.
Persona
- headroom
- -
- paig
- -
Runtime
- headroom
- -
- paig
- -
License
- headroom
- Apache-2.0
- paig
- Apache-2.0
Last pushed
- headroom
- Sep 17, 2026
- paig
- Aug 5, 2025
Categories
- headroom
- Developer Tools, Evaluation & Observability, Inference & Serving, Model Training
- paig
- Developer Tools, Evaluation & Observability
Trust and health
Maintenance
- headroom
- Very active (96%)
- paig
- Dormant (18%)
Days since push
- headroom
- 0d
- paig
- 401d
Open issues (now)
- headroom
- 671
- paig
- 57
Stars delta
- headroom
- +6.4k (30d)
- paig
- -1 (30d)
Open issues delta
- headroom
- +183 (30d)
- paig
- 0 (30d)
Full report
- headroom
- Trust report
- paig
- Trust report
Choose headroom if…
- headroom is primarily Python; paig is CSS.
- Requirements: Requires Docker; Requires Python 3.10+.; ONNX-backed features require AVX2 on x86/x86_64 hosts..
- Tags unique to headroom: agent, ai, anthropic, claude-code.
- Also covers Inference & Serving, Model Training.
- headroom ships Docker support for self-hosted deployment.
- When you need to reduce token usage for coding agents by 20% and for JSON by 60-95% without changing the answers.
When NOT to use headroom
- If you are working with environments that do not support Python 3.10+.
- When your project does not require token optimization or compression for JSON and coding agents.
- If you are working on a platform that does not support the ONNX-backed features, such as some Docker/QEMU setups or older cloud VMs without AVX2.
Choose paig if…
- paig is primarily CSS; headroom is Python.
- Tags unique to paig: compliance, genai, guardrails, security.
- You should use PAIG when you are working with generative AI applications where strict adherence to compliance protocols is necessary.
When NOT to use paig
- Avoid using PAIG if your application does not require stringent safety and security measures specific to generative AI systems.
- Do not use PAIG when working on non-generative AI projects as it is specifically tailored for GenAI applications.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (headroomlabs-ai/headroom) · observed Sep 20, 2026
- GitHub forks (headroomlabs-ai/headroom) · observed Sep 20, 2026
- Last push (headroomlabs-ai/headroom) · observed Sep 17, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 20, 2026
- GitHub stars (privacera/paig) · observed Sep 20, 2026
- GitHub forks (privacera/paig) · observed Sep 20, 2026
- Last push (privacera/paig) · observed Aug 5, 2025
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
GitHub stars on cards: headroom 73k · paig 211 (synced Sep 20, 2026).
Common questions
- What is the difference between headroom and paig?
- headroom: Compress tool outputs, logs, files, and RAG chunks before they reach the LLM.. paig: Protects Generative AI applications by ensuring security, safety, and observability. See the comparison table for live GitHub stats and shared categories.
- When should I choose headroom over paig?
- Choose headroom over paig when headroom is primarily Python; paig is CSS; Requirements: Requires Docker; Requires Python 3.10+.; ONNX-backed features require AVX2 on x86/x86_64 hosts.; Tags unique to headroom: agent, ai, anthropic, claude-code; Also covers Inference & Serving, Model Training; headroom ships Docker support for self-hosted deployment; When you need to reduce token usage for coding agents by 20% and for JSON by 60-95% without changing the answers.
- When should I choose paig over headroom?
- Choose paig over headroom when paig is primarily CSS; headroom is Python; Tags unique to paig: compliance, genai, guardrails, security; You should use PAIG when you are working with generative AI applications where strict adherence to compliance protocols is necessary.
- When should I avoid headroom?
- If you are working with environments that do not support Python 3.10+. When your project does not require token optimization or compression for JSON and coding agents. If you are working on a platform that does not support the ONNX-backed features, such as some Docker/QEMU setups or older cloud VMs without AVX2.
- When should I avoid paig?
- Avoid using PAIG if your application does not require stringent safety and security measures specific to generative AI systems. Do not use PAIG when working on non-generative AI projects as it is specifically tailored for GenAI applications.
- Is headroom or paig more popular on GitHub?
- headroom has more GitHub stars (72,850 vs 211). Stars measure visibility, not whether either tool fits your constraints.
- Are headroom and paig open source?
- Yes - both are open-source projects on GitHub (headroom: Apache-2.0, paig: Apache-2.0).
- Where can I find alternatives to headroom or paig?
- GraphCanon lists graph-backed alternatives at headroom alternatives and paig alternatives (headroom markdown twin, paig 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, headroom or paig?
- headroom: Very active. paig: Dormant. 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 headroom and paig?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: headroom trust report; paig trust report.