nowfound

Alternatives

Products that do what Aspera does

A new language for building transparent, adaptive AI

  1. 1
    Athina AI509

    Monitor LLMs and automatically detect hallucinations in prod

    2024

  2. 2
    Agenta362

    Open-source prompt management & evals for AI teams

    Nov 2025 · agenta.ai

  3. 3
    Opper AI229

    The european AI gateway for agents

    Jul 2026 · opper.ai

  4. 4
    Signs172

    Breaking down communication barriers with AI

    2025

  5. 5
    Dify.AI261

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

    2023

  6. 6PD

    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

  7. 7MA
  8. 8

    Open-source platform for enterprise AI agents, web-first.

    2025

  9. 9

    AI Agent Compute Platform

    Sep 2025

  10. 10RL

    May 2026 · adola.app

  11. 11
    Finyuus81

    A code-first language for durable, governed AI workflows

    Aug 2026 · github.com

  12. 12CT

    If agent's tools are exposed as functions/objects in a Python REPL (as opposed to JSON schemas) they perform better, I linked the explainer article we wrote, but if you want to jump straight in check out the docs! https://docs.symbolica.ai/

    Dec 2025 · symbolica.ai

  13. 13

    Fine-tuning, RL, and inference in one CLI

    Dec 2025 · github.com

  14. 14AP

    Hey all! I recently gave a workshop talk at PyCon Greece 2025 about building production-ready agent systems. To check the workshop, I put together a demo repo: (I will add the slides too soon in my blog: https://www.petrostechchronicles.com/) https://github.com/Aherontas/Pycon_Greece_2025_Presentation_... The idea was to show how multiple AI agents can collaborate using FastAPI + Pydantic-AI, with protocols like MCP (Model Context Protocol) and A2A (Agent-to-Agent) for safe communication and orchestration. Features: - Multiple agents running in containers -…

    Sep 2025 · github.com

  15. 15DA

    Hi HN, Today I'd like to present the results of my weekend project of the last year or so. Given there are many posts on HN about LLMs and Prolog, I thought that this would be of interest. DeepClause is my own (possibly misguided :-) attempt at combining LLMs with Logic Programming, ultimately hoping to establish a foundation for building more reliable agents, that produce reproducible and fully traceable result. At the heart of DeepClause is a DSL called "DeepClause Meta Language" (DML) which can be used to encode agent behaviors as executable logic programs. DML is executed by a…

    Nov 2025 · github.com

  16. 16TO
  17. 17

    Transparency in AI Logic

    Oct 2025

  18. 18MR

    The most common failures for production agents are behavioral: looping, reasoning leakage, user frustration, and more. Using a frontier model like GPT or Sonnet to judge every turn is too expensive and slow to run at scale. To solve this, we built Reflexes: semantic signals from agent traces, served fast and cheap over API. Built on custom kernels and a custom inference engine forked from vLLM. Under the hood, it is a small LLM architected around multi-head inference. Small models need to be trained for specific tasks, but running 50 separate small models on the same input for 50 tasks makes…

    Jun 2026

  19. 19

    A minimalist, modular, and versatile AI agent framework.

    Sep 2025

  20. 20LA

    We combined Stanford's ACE (agents learning from execution feedback) with the Reflective Language Model pattern. Instead of reading traces in a single pass, an LLM writes and runs Python in a sandbox to programmatically explore them - finding cross-trace patterns that single-pass analysis misses. The framework achieved 2x consistency improvement on τ2-bench.

    Mar 2026 · github.com

  21. 21AV

    I feel like LLMs can help me understand anything. However, after I get a summary, I can't dive in to parts that I find interesting; can't refer to original source easily and can't control context with chatbots. This is an attempt to solve for a complete knowledge consumption experience with AI . Please give me feedback!

    Oct 2025 · kerns.ai

  22. 22
    Aster2

    Build deterministic, multi-hop reasoning agents with Astraea

    Jun 2026 · hiveconsulting.dev

  23. 23IA

    I am working on an AI that uses multiple LLM based agents to do medical research on any topic you choose! The program terminates after a set number of iterations and all of the findings are saved. Still a work in progress but it is showing some promising results imho! Would love to receive any critical and constructive feedback, collaborate, Review your PRs, or discuss your ideas!!

    2023 · github.com

  24. 24

    We've been working on an open-source coding agent that generates code alongside machine-checkable proofs. We'd love feedback from the HN community, especially from people interested in formal verification, Lean, Dafny, or AI coding agents. Currently, only 3 langauges can be verified.

    Jul 2026 · github.com

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