Alternatives
Products that do what OrKaCore does
orchestrate cognition
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Hey HN, we're Jon and Kristiane, and we're building Orloj (https://orloj.dev), an open-source orchestration runtime for multi-agent AI systems. You define agents, tools, policies, and workflows in declarative YAML manifests, and Orloj handles scheduling, execution, governance, and reliability. Over the past year we tried to use many different platforms/frameworks to build out agent systems and while building we hit some sort of problem with all of them, so we decided to have a go at it. Jon has worked with kubernettes and terraform for years and always liked the declarative…
Mar 2026 · github.com
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A brief overview: 1. Workflows steps share a running context, with access to data they need require. 2. Steps in the workflow (builders) are chained together based on a topologically sorted built from the predefined input & output. 3. No servers spin up (like Conductor/Cadence) - the orchestrator is low level and meant for simplifying business logic. 4. Before/After listeners for each step. Would love to hear your thoughts and feedback!
2024 · github.com
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At Cajal (YC W26) we’re excited to share Talos (https://github.com/cajal-technologies/talos), an open source framework for formal verification of WebAssembly modules in Lean. AI is now writing tons of the code that gets pushed to production. As code generation gets cheaper, verification becomes the bottleneck. We believe in a future where every piece of software comes with a mathematical proof that it does what its author intended - in doing so, eliminating many classes of exploits. Talos is part of the foundation for that. Talos provides a Wasm interpreter optimized for…
Jun 2026 · github.com
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I think like many of you, I've been jumping between many claude code/codex sessions at a time, managing multiple lines of work and worktrees in multiple repos. I wanted a way to easily manage multiple lines of work and reduce the amount of input I need to give, allowing the agents to remove me as a bottleneck from as much of the process as I can. So I built an orchestration tool for AI coding agents: Optio is an open-source orchestration system that turns tickets into merged pull requests using AI coding agents. You point it at your repos, and it handles the full lifecycle: - Intake —…
Mar 2026 · github.com
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OrchestraML▲82From English prompt to deployed ML model with human approval
Jun 2026 · orchestra-ml.vercel.app
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a flexible threat detection platform that simplifies rule execution and management with k8s cronJobs and helm. flexible enough to run standalone or with other schedulers like hashicorp nomad.
2024 · github.com
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Hey HN! I’m the founder of Unify, and we’ve just released our Model Hub, which provides a collection of LLM endpoints with live runtime benchmarks all plotted across time: https://unify.ai/hub A key finding is that static tabular runtime benchmarks for LLMs simply do not work. It’s necessary to take a time-series perspective, and plot the variations through time. We currently have 21 models provided by: Anyscale, Perplexity AI, Replicate, Together AI, OctoAI, Mistral AI and OpenAI, with more on the roadmap. We test across different regions (Asia, US, Europe), with varied…
2024
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2022 · github.com
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Hey Folks! I've been building an open source benchmark for measuring local LLM performance on your own hardware. The benchmarking tool is a CLI written on top of Llamafile to allow for portability across different hardware setups and operating systems. The website is a database of results from the benchmark, allowing you to explore the performance of different models and hardware configurations. Please give it a try! Any feedback and contribution is much appreciated. I'd love for this to serve as a helpful resource for the local AI community. For more check out: - Website:…
2025 · localscore.ai
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Hey HN! I'm Caleb, one of the contributors to Opik, a new open source framework for LLM evaluations. Over the last few months, my colleagues and I have been working on a project to solve what we see as the most painful parts of writing evals for an LLM application. For this initial release, we've focused on a few core features that we think are the most essential: - Simplifying the implementation of more complex LLM-based evaluation metrics, like Hallucination and Moderation. - Enabling step-by-step tracking, such that you can test and debug each individual component of your LLM application,…
2024 · github.com
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Hey HN! I'm excited to introduce Symphony – a toolkit designed to help developers write functions and let GPT-4 call them in whatever sequence that makes most sense based on conversation. I've been quite amazed[1] by GPT-4's recent ability to both detect when a function needs to be called and to respond with JSON that adheres to the function's signature. Since developers currently append descriptions of functions to API calls[2], I often found myself wishing for a toolkit that would automatically create these descriptions as I added and debugged functions during development. You can get…
2023 · symphony.run
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Hi HN! We're Gabriel & Viraj, and we're excited to open source TensorZero. To be a little cheeky, TensorZero is an open-source platform that helps LLM applications graduate from API wrappers into defensible AI products. 1. Integrate our model gateway 2. Send metrics or feedback 3. Unlock compounding improvements in quality, cost, and latency It enables a data & learning flywheel for LLMs by unifying: • Inference: one API for all LLMs, with <1ms P99 overhead • Observability: inference & feedback → your database • Optimization: better prompts, models, inference strategies • Experimentation:…
2024 · github.com
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