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Alternatives

Products that do what Wolfram Language 15 does

Computational language built for humans and AI agents

  1. 1

    Knowledge-based programming

    2014

  2. 2

    Find your best LLM for a local inference

    2023

  3. 3

    Visualizing daily LLM papers

    2024

  4. 4

    A catalogue of artificial intelligence APIs by Microsoft

    2015

  5. 5
    Colossal135

    Effortlessly integrate tool-using agents with a single fetch

    2025

  6. 6
    PaLM 2247

    Google's next generation large language model

    2023

  7. 7

    The first no-code autonomous agents management platform

    2023

  8. 8
    Lunagraph162

    Your design canvas that writes code powered by AI

    Apr 2026

  9. 9

    AI engine created for developers w/ a visual editor + APIs

    2015

  10. 10

    Build local LLMs using top data science libraries

    2023

  11. 11

    A web code editor with AI & multi-language support

    2025

  12. 12
    Cosine175

    Your AI Co-developer - Not just an LLM Wrapper

    2023

  13. 13
    Minicule121

    Use AI to visualize biomedical knowledge

    2025

  14. 14
    Raijin.ai137

    Write reports and synthesize data rapidly with AI

    2024

  15. 15

    All AI/LLM related updates in one place

    2023

  16. 16

    An LLM framework for large scale code migrations

    2025

  17. 17

    The world's first illustrated LLM

    2025

  18. 18GB

    Hey HN, We’re excited to share PySpur, an open-source tool that provides a graph-based interface for building, debugging, and evaluating LLM workflows. Why we built this: Before this, we built several LLM-powered applications that collectively served thousands of users. The biggest challenge we faced was ensuring reliability: making sure the workflows were robust enough to handle edge cases and deliver consistent results. In practice, achieving this reliability meant repeatedly: 1. Breaking down complex goals into simpler steps: Composing prompts, tool calls, parsing steps, and branching…

    2024 · github.com

  19. 19WC

    Hi all, I'm Ivan, and together with Alex, we're building a diagram visualization tool for codebases. Alex and I are devs, and we've noticed that recently we've been super productive at writing code (prompting :D). But when it comes to understanding big systems, prompting doesn't work that well — for that, diagrams are best imo. Most tools out there don't scale to big projects (e.g. PyTorch), so we're building CodeBoarding — a recursive visualizer for codebases. It starts from the highest level of abstractions and lets you dive deeper. We use static analysis and LLM agents. The control-flow…

    2025 · github.com

  20. 20LB

    Hello everyone. I built an AI-based toolset to help me with language learning. I wanted to be able to easily generate very specific study content and get rapid feedback on my writing. Unlike most language apps, it doesn’t actually try to teach you a language. Instead, it’s a collection of tools for people at an intermediate level who already have a learning process It’s particularly great for Anki users. There a demo video on the login page, and I set up anonymous auth for people who want to test it without creating an account. Feedback and bug reports welcome.

    2025 · drillapp.xyz

  21. 21LI

    2018 · languagemodels.io

  22. 22AU

    Agentpanel is an observability platform for optimizing the control flow, performance, token usage, and correctness of LLM/AI agents! Built-in @rustlang, the first release of Agent Panel currently features an AI gateway that provides seamless access to 100+ LLMs across 20+ platforms, including OpenAI GPT-4o, Gemini 1.5 Pro latest, AnthropicAI Claude 3.5, MistralAI, Cohere, Groq,Perplexity AI, and more.

    2024 · github.com

  23. 23CA

    Hey there HN! We're Vivek and Si-Yan from Cartograph (https://cartograph.app). We've built an AI-powered code documentation platform that automatically generates reference documentation and creates a visual interactive map of the codebase that serves as both high level architecture diagram and allows you to zoom in to specific implementations. How it works: We use static analysis to read a codebase and get its symbols and their dependencies, creating a complete map that includes function calls. We use LLMs (Gemini + Claude) to add metadata to this map, as well as augment it in…

    2024 · cartograph.app

  24. 24LF

    Hey HN, I built SWE-Kit, LLM toolkit (Function callable tools) which makes building agents specialised in coding like Devin very easy. I noticed a typical pattern while building local agents: creating & perfecting LLM tools to interact with system or codebase was the repeated and time-consuming. We created a layer that simplifies building agents that can interact with code, file system, git, shell and allows you to quickly solve for a wide variety of coding agent use cases. Aren’t there open coding agents already? Well, yes, but most folks would want to solve their specific use case like a…

    2024 · swekit.dev

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