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AI · alternatives · 2026

24 alternatives to Instill VDP

Open source unstructured data ETL for AI first applications

Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Prices are shown for the 1 we have checked on their own sites, 1 of them free or with a free tier. Instill VDP launched in 2024; newer entries below may have overtaken it.

  1. 1

    Hi HN - We're Ping-Lin and Xiaofei from Instill AI (https://www.instill.tech). We're building VDP (https://github.com/instill-ai/vdp), an open-source ETL tool for unstructured visual data. When people say they are data-driven, most of the time it means they are driven by structured data. I will cut the part where we cite reports claiming that 80% of data are unstructured. The reality is unstructured data are more difficult to analyse and not a lot of companies know or have the resources to deal with them. Before starting Instill AI, we were in a smart video…

    2022 · github.com · its alternatives →

  2. 2

    Automate your document workflows

    2024 · panda-etl.ai · its alternatives →

  3. 3OS

    Complete AI Platform: RAG Systems & Intelligent Agents for Local AI

    2025 · rlama.dev · its alternatives →

  4. 4

    Open-source foundation of ToolJet AI - the enterprise app generation platform for internal tools, dashboards, business applications, workflows and AI agents. Build visually, from a prompt, or from Claude Code, Codex and Cursor over MCP 🚀 - ToolJet/ToolJet

    2021 · github.com · its alternatives →

  5. 5

    🧙 Build, run, and manage data pipelines for integrating and transforming data. - mage-ai/mage-ai

    2022 · github.com · its alternatives →

  6. 6

    data-to-paper: Backward-traceable AI-driven scientific research - Technion-Kishony-lab/data-to-paper

    2024 · github.com · its alternatives →

  7. 7
    Dify.AI▲261

    Open-source platform for LLMOps, define your AI-native apps

    2023 · dify.ai · its alternatives →

  8. 8

    Make any data RAG-ready in seconds

    2025 · its alternatives →

  9. 9
    Cortexfree▲306

    Turn API specs into docs, SDKs, and MCP servers

    Sep 2026 · cortexdocs.dev · its alternatives →

  10. 10

    Data processing infra & ETL for generative AI applications

    2024 · contextdata.ai · its alternatives →

  11. 11AA

    Find information, resources and relevant links for tripl.ai. This domain may be for sale.

    2021 · arc.tripl.ai · its alternatives →

  12. 12

    Documind is an open-source tool that turns documents into structured data using AI. What it does: - Extracts specific data from PDFs based on your custom schema - Returns clean, structured JSON that's ready to use - Works with just a PDF link + your schema definition Just run npm install documind to get started.

    2024 · github.com · its alternatives →

  13. 13

    Hi HN, I’ve been working on an OCR pipeline specifically optimized for machine learning dataset preparation. It’s designed to process complex academic materials — including math formulas, tables, figures, and multilingual text — and output clean, structured formats like JSON and Markdown. Some features: • Multi-stage OCR combining DocLayout-YOLO, Google Vision, MathPix, and Gemini Pro Vision • Extracts and understands diagrams, tables, LaTeX-style math, and multilingual text (Japanese/Korean/English) • Highly tuned for ML training pipelines, including dataset generation and…

    2025 · github.com · its alternatives →

  14. 14

    Open-source foundation of ToolJet AI - the enterprise app generation platform for internal tools, dashboards, business applications, workflows and AI agents. Build visually, from a prompt, or from Claude Code, Codex and Cursor over MCP 🚀 - Release v2.0.0 · ToolJet/ToolJet

    2023 · github.com · its alternatives →

  15. 15

    Get your unstructured data AI-ready in minutes

    2024 · tonic.ai · its alternatives →

  16. 16

    We’re Robin, Louis, and Thomas. Pipelex is a DSL and a Python runtime for repeatable AI workflows. Think Dockerfile/SQL for multi-step LLM pipelines: you declare steps and interfaces; any model/provider can fill them. Why this instead of yet another workflow builder? - Declarative, not glue code: you state what to do; the runtime figures out how. - Agent-first: each step carries natural-language context (purpose, inputs/outputs with meaning) so LLMs can follow, audit, and optimize. Our MCP server enables agents to run pipelines but also to build new pipelines on demand. - Open…

    Oct 2025 · github.com · its alternatives →

  17. 17

    Mage AI helps data teams build, orchestrate, monitor, and repair production data pipelines with editable SQL and Python for analytics, applications, and AI.

    2022 · mage.ai · its alternatives →

  18. 18
    HFlow▲91

    Scalable multimodal data pipelines for robotics

    Aug 2026 · github.com · its alternatives →

  19. 19OS
  20. 20

    ZenML 🙏: One AI Platform from Pipelines to Agents. https://zenml.io. - zenml-io/zenml

    2020 · github.com · its alternatives →

  21. 21

    open-source agentic AI data assistant for the next generation of AI + Data products. - eosphoros-ai/DB-GPT

    2023 · github.com · its alternatives →

  22. 22

    Hey HN, I wanted to share a new project we've been working on for the last couple of months called ART (https://github.com/OpenPipe/ART). ART is a new open-source framework for training agents using reinforcement learning (RL). RL allows you to train an agent to perform better at any task whose outcome can be measured and quantified. There are many excellent projects focused on training LLMs with RL, such as GRPOTrainer (https://huggingface.co/docs/trl/main/en/grpo_trainer) and verl…

    2025 · github.com · its alternatives →

  23. 23
    Vext▲113

    Quick custom AI from your data out-of-the-box

    2023 · its alternatives →

  24. 24

    The traditional pipeline for unstructured data extraction typically follows these steps: 1. Image → OCR Model (e.g., Google Vision) → Layout Model (e.g. Surya) → LLM → Final Answer However, this can be streamlined using a Vision-Language Model (VLM): 2. Image → VLM → Final Answer Recently VLMs have improved a lot for OCR and document understanding tasks, specifically the Qwen-2.5-VL series. We can run the Qwen-2.5-VL-7B-AWQ model locally with just 16GB VRAM, and perform end-to-end information extraction (fields and table extraction) without any external models. Hallucination with VLMs One…

    2025 · github.com · its alternatives →

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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →