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AI · alternatives · 2026

24 alternatives to SED (Semantic Entities Designs)

LLM-native semantic layer for your database.

Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.

  1. 1
    SeDQL▲1

    Make your database understandable to AI. Local. Fast. Free.

    Aug 2026 · sedql-website.vercel.app · its alternatives →

  2. 2

    Write SQL without knowing SQL

    2023 · supabase.com · its alternatives →

  3. 3

    Find your best LLM for a local inference

    2023 · its alternatives →

  4. 4

    I spent a few hours last weekend testing whether AI can replace code by executing directly. Built a contact manager where every HTTP request goes to an LLM with three tools: database (SQLite), webResponse (HTML/JSON/JS), and updateMemory (feedback). No routes, no controllers, no business logic. The AI designs schemas on first request, generates UIs from paths alone, and evolves based on natural language feedback. It works—forms submit, data persists, APIs return JSON—but it's catastrophically slow (30-60s per request), absurdly expensive ($0.05/request), and has zero UI…

    Nov 2025 · github.com · its alternatives →

  5. 5

    Build data processing and data analysis pipelines that leverage the power of LLMs 🧠 - anishathalye/semlib

    2025 · github.com · its alternatives →

  6. 6

    Write SQL & analyze data with ai

    2024 · chat2db.ai · its alternatives →

  7. 7

    Compare AI models easily! All providers in one place. Find the best LLM for your needs with our comprehensive pricing calculator and feature comparison tool. OpenAI, Anthropic, Google, and more.

    2024 · countless.dev · its alternatives →

  8. 8

    I built this tool because I wanted a way to just take a bunch of URLs or domains, and query their content in RAG applications. It takes away the pain of crawling, extracting content, chunking, vectorizing, and updating periodically. I'm curious to see if it can be useful to others. I meant to launch this six months ago but life got in the way...

    2024 · embedding.io · its alternatives →

  9. 9

    A pure ORM for writing native SQL queries yielding pure business objects - craigmichaelmartin/pure-orm

    2021 · github.com · its alternatives →

  10. 10

    Local first semantic and hybrid BM25 grep / search tool for use by AI and humans! - GitHub - BeaconBay/ck: Local first semantic and hybrid BM25 grep / search tool for use by AI and humans!

    2025 · github.com · its alternatives →

  11. 11

    I've been exploring the (not so=) amazing potential of AI in coding and have compiled a list of tools. From AI-powered IDEs to code generators, this resource is my contribution to the community. I'm still on the fence about including txt2sql projects, as their functionality seems too basic to me. And I'm personally maintaining this, so your feedback is wellcome.

    2025 · aicode.danvoronov.com · its alternatives →

  12. 12

    sed to C translator written in sed. Contribute to lhoursquentin/sed-bin development by creating an account on GitHub.

    2020 · github.com · its alternatives →

  13. 13

    Get your unstructured data AI-ready in minutes

    2024 · tonic.ai · its alternatives →

  14. 14

    Built this for my LLM workflows - needed searchable, persistent memory that wouldn't blow up storage costs. I also wanted to use it locally for my research. It's a content-addressed storage system with block-level deduplication (saves 30-40% on typical codebases). I have integrated the CLI tool into most of my workflows in Zed, Claude Code, and Cursor, and I provide the prompt I'm currently using in the repo. The project is in C++ and the build system is rough around the edges but is tested on macOS and Ubuntu 24.04.

    2025 · github.com · its alternatives →

  15. 15

    Hey HN, I made Browser-Use, an open-source tool that lets (all Langchain supported) LLMs execute tasks directly in the browser just with function calling. It allows you to build agents that interact with web elements using natural language prompts. We created a layer that simplifies website interaction for LLMs by extracting xPaths and interactive elements like buttons and input fields (and other fancy things). This enables you to design custom web automation and scraping functions without manual inspection through DevTools. Hasn't this been done a lot of times? Good question, as a general…

    2024 · github.com · its alternatives →

  16. 16

    Hi folks. I've been doing some experiments on how LLMs could get more handy in the day to day of working with files (CSV, Parquet, etc). Earlier last year, I built https://datakit.page and evolved it over and over into an all in-browser experience with help of duckdb-wasm. Got loads of feedbacks and I think it turned into a good shape with being an adhoc local data studio, but I kept hearing two main things/issues: Why can't the AI also change cells in the file we give to it? Why can't we modify this grid ourselves? So besides the whole READ and text-to-SQL flows, what seemed…

    Feb 2026 · opensheet.app · its alternatives →

  17. 17

    Embed NL-to-SQL into your product

    2024 · its alternatives →

  18. 18

    Hi Hacker News! We’re Vadim and Chris from Highlight.io [1]. We do web app monitoring and are working on using LLMs/embeddings to add new functionality to our error monitoring product. Given that there’s a lot of founders/engineers using LLMs in their products, we figured we’d share how we built the new functionality, their impact on our workflows, and how you can try it out. Our goal was to build two features: (1) tagging errors (e.g. deeming an error as “authentication error” or a “database error”); and (2) grouping similar errors together (e.g. two errors that have a different…

    2023 · github.com · its alternatives →

  19. 19NL

    Hi HN- Today, we are releasing the hosted API for our natural language to SQL engine, which allows you to: (1) Explain Your Data: Feed in dictionaries, dbt, schemas, Confluence docs - we'll understand the business context to your data. (2) Train Your AI: Fine-tune an LLM (including GPT-4) specifically for your data, increasing accuracy and lowering latency (3) Trust the Answer: See confidence scores with each AI-generated query, stay in control. (4) Conduct complex SQL queries Problem background - Developers struggle to build NL-to-SQL into products because LLMs do not work out-of-the-box;…

    2024 · dataherald.com · its alternatives →

  20. 20

    A repository that contains models, datasets, and fine-tuning techniques for DB-GPT, with the purpose of enhancing model performance in Text-to-SQL - eosphoros-ai/DB-GPT-Hub

    2023 · github.com · its alternatives →

  21. 21

    G'day, HN! I'm one of the maintainers of `llm`. I've been working alongside a trusty group of contributors to bring this project to life, and we're now at a point where we're ready to share it with the world. Large language models (LLMs) are taking the computing world by storm due to their emergent abilities that allow them to perform a wide variety of tasks, including translation, summarization, code generation, and even some degree of reasoning. However, the ecosystem around LLMs is still in its infancy, and it can be difficult to get started with these models. `llm` is a one-stop shop for…

    2023 · github.com · its alternatives →

  22. 22LA

    Hi HN, I made Lingo - the SQLite of semantic search. I'm a self-taught developer and researcher who left school at 16, and I've spent some time exploring a first-principles approach to system design for various frontier problems. In this case it's AI that challenges the 'bigger is better' transformer paradigm. Lingo is the first piece of that research, a high-performance linguistic database designed to run on-device. The full technical overview and manifesto is here: https://medium.com/@robm.antunes/bcd1e9752af6 The paper has been archived on Zenodo with a DOI:…

    2025 · its alternatives →

  23. 23

    Hi HN, Working with multiple projects, I got tired of re-explaining our complex multi-node system to LLMs. Documentation helped, but plain text is hard to search without indexing and doesn't work across projects. I built Linggen to solve this. My Workflow: I use the Linggen VS Code extension to "init my day." It calls the Linggen MCP to load memory instantly. Linggen indexes all my docs like it’s remembering them—it is awesome. One click loads the full architectural context, removing the "cold start" problem. The Tech: Local-First: Rust + LanceDB. Code and embeddings stay on your machine. No…

    Dec 2025 · github.com · its alternatives →

  24. 24

    Database LLM Wrapper

    2025 · 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 →