nowfound

Alternatives

Products that do what Orcred does

The live technical verification standard for AI/ML engineers

  1. 1

    Ship AI Code with confidence and speed

    2024

  2. 2
    Cred97

    OAuth credential delegation for AI agents

    Apr 2026

  3. 3

    Find engineers who never apply by actual github code

    Mar 2026

  4. 4
    Redential116

    A developer credential that proves what you built, NDA safe.

    Jul 2026 · redential.com

  5. 5

    Your coding agent’s testing buddy

    17d ago · checksum.ai

  6. 6

    Non-KYC Identity Verification Platform for Creators

    2021

  7. 7

    Give AI access to 6754+ APIs with zero credentials exposed

    Feb 2026

  8. 8
    AI or Not164

    Detect AI generated images, audio & KYC documents for free.

    2024

  9. 9
    Skilled76

    Dashboard to find agent skills you no longer need

    May 2026

  10. 10
    Cyris98

    Turns every AI decision into audit-ready evidence

    Apr 2026

  11. 11
    Latchkey122

    Credential layer for local AI agents

    Mar 2026

  12. 12

    Measure how much of your code is AI-generated. Open source.

    Apr 2026

  13. 13

    Verify your job-ready skills with AI in 60 seconds

    5d ago · skilluparc.com

  14. 14
    Verify120

    Test out ideas before you implement them.

    2015

  15. 15
    Qodex88

    Discover, Test & Secure Your APIs — 10x Faster with AI.

    2025

  16. 16

    Your AI security engineer. Ship fast while staying secure.

    Apr 2026

  17. 17

    New Age. Instant. <$1 Verification.

    2025

  18. 18IB

    For the last 6 months, I've been building ORUS Builder, an open-source AI code generator. My goal was to fix the biggest issue I have with tools like v0, Lovable, etc. – they generate broken, non-compiling code that needs hours of debugging. ORUS Builder is different. It uses a "Compiler-Integrity Generation" (CIG) protocol, a set of cognitive validation steps that run before the code is generated. The result is a 99.9% first-time compilation success rate in my tests. The workflow is simple: 1.Describe an app in a single prompt. 2.It generates a full-stack application…

    Nov 2025

  19. 19
    Mantyl8

    Hand over AI-built software with proof

    5d ago · mantyl.dev

  20. 20LO

    Hi HN, Martin, Nils, and Jannes here. We are building Legit, an open source version control and collaboration layer for AI agents and AI native applications. You can find the repo here https:&#x2F;&#x2F;github.com&#x2F;Legit-Control&#x2F;monorepo and the website here https:&#x2F;&#x2F;legitcontrol.com Over the last years, we worked on multiple developer tools and AI driven products. As soon as we started letting agents modify real files and business critical data, one problem kept showing up. We could not reliably answer what changed, why it changed, or how to safely undo it. Today, most AI…

    Jan 2026

  21. 21WA

    Today you can easily adopt AI coding tools because you have git for branching and rolling back if AI writes bad code. We haven't seen this same capability for data and decided to build it ourselves. Nile is a new kind of data lake, purpose built for using with AI. It can act as your data engineer or data analyst creating new tables and rolling back bad changes in seconds. We support real versions for data, schema, and ETL. We'd love your feedback on any part of what we are building - https:&#x2F;&#x2F;getnile.ai&#x2F; What do you think?

    Jan 2026

  22. 22VA

    Hi all, Gorkem here. I started VerifyWise [1] to make AI governance less painful. Today, we’re launching our open-source platform to help teams take control of their AI compliance process. VerifyWise helps organizations navigate AI governance by providing audit readiness, risk registers, model fairness checks, and compliance documentation. Those are all built into a single platform you can self-host. We’ve been quietly building VerifyWise for a while, and we’re now at a place where it’s ready for more teams to try. Since we started, we've: - Released our core platform on GitHub:…

    2025 · verifywise.ai

  23. 23SM

    I work as an engineer at the Dutch government. We have hundreds of technical standards that developers should follow when building government software: API design rules, messaging protocols, authentication profiles, accessibility requirements. The problem is that most developers don't know these standards exist until someone reviews their code (if at all). Skills are Markdown files that inject domain knowledge into AI coding tools. When a developer starts building an API, the tool automatically loads the relevant standard. No plugins to write, no code. Just structured knowledge in Markdown.…

    Feb 2026 · anneschuth.nl

  24. 24MD

    We’re excited to share ML-Dev-Bench, a new open-source benchmark that tests AI agents on real-world ML development tasks. Unlike typical coding challenges or Kaggle-style competitions, our benchmark simulates end-to-end ML workflows including: - Dataset handling and preprocessing - Debugging model and code failures - Implementing new model architectures - Fine-tuning and improving existing models With 30 diverse tasks, ML-Dev-Bench evaluates agents across critical stages of ML development. To complement this, we built Calipers, a framework that provides systematic performance evaluation and…

    2025 · github.com

Ranked by how close each launch is in meaning, then by votes. Refine with a description →