--- title: "txtai vs unstract" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/neuml-txtai-vs-zipstack-unstract" tools: ["neuml-txtai", "zipstack-unstract"] --- # txtai vs unstract *GraphCanon updated Aug 16, 2026* ## Verdict Pick txtai if txtai offers a comprehensive suite for semantic search and large language model workflows. Ideal for those who require an all-in-one framework with embedding generation and information retrieval capabilities; 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. [txtai](https://neuml.github.io/txtai) reports 13k GitHub stars, 873 forks, and 10 open issues, last pushed Aug 12, 2026. [unstract](https://unstract.com) has 6.9k stars, 663 forks, and 88 open issues, last pushed Jul 27, 2026. Figures are from public GitHub metadata via [txtai's repository](https://github.com/neuml/txtai) and [unstract's repository](https://github.com/Zipstack/unstract). | | [txtai](/tools/neuml-txtai.md) | [unstract](/tools/zipstack-unstract.md) | | --- | --- | --- | | Tagline | All-in-one AI framework for semantic search, LLM orchestration and language model workflows | LLM-Driven Extraction of Unstructured Data for API Deployments and ETL Pipeline Workflows | | Stars | 12,890 | 6,932 | | Forks | 873 | 663 | | Open issues | 10 | 88 | | Language | Python | Python | | Adopt for | Txtai offers a comprehensive suite for semantic search and large language model workflows. Ideal for those who require an all-in-one framework with embedding generation and information retrieval capabilities. | 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 | - | - | | Runtime | - | - | | License | Apache-2.0 | AGPL-3.0 | | Categories | AI Agents, Data & Retrieval, LLM Frameworks | Data & Retrieval, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [txtai](/tools/neuml-txtai.md) | [unstract](/tools/zipstack-unstract.md) | | --- | --- | --- | | Days since push | 3d | 0d | | Open issues (now) | 10 | 88 | | Stars delta | +162 (30d) | Unknown | | Open issues delta | -8 (30d) | Unknown | | Full report | [trust report](/tools/neuml-txtai/trust.md) | [trust report](/tools/zipstack-unstract/trust.md) | ## Decision facts: txtai - **Pricing:** freemium - Txtai is open-source under the Apache-2.0 license allowing free usage along with modification for personal and commercial projects. However, it doesn't come with dedicated support packages which can旗子 - **Requirements:** Min 4 GB RAM; Development and use of txtai require a Python environment set up on your machine. - **Adopt for:** Txtai offers a comprehensive suite for semantic search and large language model workflows. Ideal for those who require an all-in-one framework with embedding generation and information retrieval capabilities. ## Decision facts: unstract - **Adopt for:** 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. ## Choose when ### Choose txtai if… - License: txtai is Apache-2.0, unstract is AGPL-3.0. - Pricing: Txtai is open-source under the Apache-2.0 license allowing free usage along with modification for personal and commercial projects. However, it doesn't come with dedicated support packages which can旗子. - Requirements: Min 4 GB RAM; Development and use of txtai require a Python environment set up on your machine.. - Tags unique to txtai: embeddings, information-retrieval, language-model, large language models. - Also covers AI Agents. - When you need a cohesive, unified solution that doesn't require integration across multiple frameworks – txtai bundles semantic search and LLM orchestration. ### Choose unstract if… - License: unstract is AGPL-3.0, txtai is Apache-2.0. - Tags unique to unstract: data-engineering, document-ai, generative-ai, idp. - You prioritize open-source contributions and require the flexibility of the AGPL-3.0 license. ## When NOT to use txtai - When you specifically need a framework with focus on advanced machine learning models beyond NLP, as txtai primarily focuses on semantic search and LLM workflows. - If your project requires customization of every single component of the AI pipeline from scratch, txtai's all-in-one approach might limit that flexibility. ## 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. ## Common questions ### What is the difference between txtai and unstract? txtai: All-in-one AI framework for semantic search, LLM orchestration and language model workflows. 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 txtai over unstract? Choose txtai over unstract when License: txtai is Apache-2.0, unstract is AGPL-3.0; Pricing: Txtai is open-source under the Apache-2.0 license allowing free usage along with modification for personal and commercial projects. However, it doesn't come with dedicated support packages which can旗子; Requirements: Min 4 GB RAM; Development and use of txtai require a Python environment set up on your machine.; Tags unique to txtai: embeddings, information-retrieval, language-model, large language models; Also covers AI Agents; When you need a cohesive, unified solution that doesn't require integration across multiple frameworks – txtai bundles semantic search and LLM orchestration. ### When should I choose unstract over txtai? Choose unstract over txtai when License: unstract is AGPL-3.0, txtai is Apache-2.0; Tags unique to unstract: data-engineering, document-ai, generative-ai, idp; You prioritize open-source contributions and require the flexibility of the AGPL-3.0 license. ### When should I avoid txtai? When you specifically need a framework with focus on advanced machine learning models beyond NLP, as txtai primarily focuses on semantic search and LLM workflows. If your project requires customization of every single component of the AI pipeline from scratch, txtai's all-in-one approach might limit that flexibility. ### 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 txtai or unstract more popular on GitHub? txtai has more GitHub stars (12,890 vs 6,932). Stars measure visibility, not whether either tool fits your constraints. ### Are txtai and unstract open source? Yes - both are open-source projects on GitHub (txtai: Apache-2.0, unstract: AGPL-3.0). ### Where can I find alternatives to txtai or unstract? GraphCanon lists graph-backed alternatives at [txtai alternatives](/tools/neuml-txtai/alternatives) and [unstract alternatives](/tools/zipstack-unstract/alternatives) ([txtai markdown twin](/tools/neuml-txtai/alternatives.md), [unstract markdown twin](/tools/zipstack-unstract/alternatives.md)), 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](/compare/neuml-txtai-vs-zipstack-unstract.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, txtai or unstract? txtai: Very active. 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 txtai and unstract? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [txtai trust report](/tools/neuml-txtai/trust); [unstract trust report](/tools/zipstack-unstract/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=neuml-txtai`](/api/graphcanon/graph?tool=neuml-txtai) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_