Comparison
annotateai vs unstract
Verdict
Pick annotateai if annotateai uses LLMs to automate the annotation of scientific and medical papers. It's open-source under Apache-2.0, categorized as an LLM Framework and Data & Retrieval tool; pick unstract if unstract is a Python-driven tool for transforming unstructured data into structured formats using OCR, PDF extraction, and other techniques to integrate with APIs and ETL workflows under AGPL-3.0.
Markdown twin · annotateai alternatives · unstract alternatives
GraphCanon updated Oct 4, 2026
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Trust & integrity
| Signal | annotateai | unstract |
|---|---|---|
| Maintenance | Slowing (137d since push) As of Sep 20, 2026 · github_public_v1 | Very active (1d since push) As of Sep 20, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 20, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 20, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 | No lockfile (source not queried) As of Oct 4, 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
- annotateai
- Automatically annotate papers using LLMs
- unstract
- LLM-Driven Extraction of Unstructured Data for API Deployments and ETL Pipeline Workflows
Stars
- annotateai
- 426
- unstract
- 7.2k
Forks
- annotateai
- 43
- unstract
- 718
Open issues
- annotateai
- 0
- unstract
- 95
Language
- annotateai
- Python
- unstract
- Python
Adopt for
- annotateai
- annotateai uses LLMs to automate the annotation of scientific and medical papers. It's open-source under Apache-2.0, categorized as an LLM Framework and Data & Retrieval tool.
- unstract
- Unstract is a Python-driven tool for transforming unstructured data into structured formats using OCR, PDF extraction, and other techniques to integrate with APIs and ETL workflows under AGPL-3.0 license.
Persona
- annotateai
- -
- unstract
- -
Runtime
- annotateai
- -
- unstract
- -
License
- annotateai
- Apache-2.0
- unstract
- AGPL-3.0
Last pushed
- annotateai
- May 5, 2026
- unstract
- Sep 18, 2026
Categories
- annotateai
- Data & Retrieval, LLM Frameworks
- unstract
- Data & Retrieval, LLM Frameworks
Trust and health
Maintenance
- annotateai
- Slowing (36%)
- unstract
- Very active (96%)
Days since push
- annotateai
- 137d
- unstract
- 1d
Open issues (now)
- annotateai
- 0
- unstract
- 95
Stars delta
- annotateai
- +4 (30d)
- unstract
- +313 (30d)
Open issues delta
- annotateai
- 0 (30d)
- unstract
- +7 (30d)
Full report
- annotateai
- Trust report
- unstract
- Trust report
Choose annotateai if…
- License: annotateai is Apache-2.0, unstract is AGPL-3.0.
- Tags unique to annotateai: ai, artificial-intelligence, large-language-models, machine-learning.
- Need automated annotations for large volumes of scientific or medical papers
When NOT to use annotateai
- Require detailed, custom annotations that go beyond general LLML capabilities
- Situations where regulatory approval necessitates human review over machine-generated annotations
Choose unstract if…
- License: unstract is AGPL-3.0, annotateai is Apache-2.0.
- Tags unique to unstract: ai-agents, data-engineering, document-ai, generative-ai.
- You prioritize open-source contributions and require the flexibility of the AGPL-3.0 license.
When NOT to use unstract
- Your workflow strictly adheres to closed-source software management policies and requires proprietary control.
- Projects needing direct integration with commercial data processing services incompatible with AGPL-3.0 licensing.
- Cases where real-time performance is critical, as the LLM-driven extraction may introduce latency.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (neuml/annotateai) · observed Sep 20, 2026
- GitHub forks (neuml/annotateai) · observed Sep 20, 2026
- Last push (neuml/annotateai) · observed May 5, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (Zipstack/unstract) · observed Sep 20, 2026
- GitHub forks (Zipstack/unstract) · observed Sep 20, 2026
- Last push (Zipstack/unstract) · observed Sep 18, 2026
- License file (AGPL-3.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Oct 4, 2026
GitHub stars on cards: annotateai 426 · unstract 7.2k (synced Sep 20, 2026).
Common questions
- What is the difference between annotateai and unstract?
- annotateai: Automatically annotate papers using LLMs. unstract: LLM-Driven Extraction of Unstructured Data for API Deployments and ETL Pipeline Workflows. See the comparison table for live GitHub stats and shared categories.
- When should I choose annotateai over unstract?
- Choose annotateai over unstract when License: annotateai is Apache-2.0, unstract is AGPL-3.0; Tags unique to annotateai: ai, artificial-intelligence, large-language-models, machine-learning; Need automated annotations for large volumes of scientific or medical papers.
- When should I choose unstract over annotateai?
- Choose unstract over annotateai when License: unstract is AGPL-3.0, annotateai is Apache-2.0; Tags unique to unstract: ai-agents, data-engineering, document-ai, generative-ai; You prioritize open-source contributions and require the flexibility of the AGPL-3.0 license.
- When should I avoid annotateai?
- Require detailed, custom annotations that go beyond general LLML capabilities Situations where regulatory approval necessitates human review over machine-generated annotations
- When should I avoid unstract?
- Your workflow strictly adheres to closed-source software management policies and requires proprietary control. Projects needing direct integration with commercial data processing services incompatible with AGPL-3.0 licensing. Cases where real-time performance is critical, as the LLM-driven extraction may introduce latency.
- Is annotateai or unstract more popular on GitHub?
- unstract has more GitHub stars (7,245 vs 426). Stars measure visibility, not whether either tool fits your constraints.
- Are annotateai and unstract open source?
- Yes - both are open-source projects on GitHub (annotateai: Apache-2.0, unstract: AGPL-3.0).
- Where can I find alternatives to annotateai or unstract?
- GraphCanon lists graph-backed alternatives at annotateai alternatives and unstract alternatives (annotateai markdown twin, unstract 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, annotateai or unstract?
- annotateai: Slowing. unstract: 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 annotateai and unstract?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: annotateai trust report; unstract trust report.