Alternatives
Products that do what Logcat.ai:AI-powered observability for Operating Systems(Android+Linux) does
Hello HN! I'm an Android OS engineer. I've worked with AOSP and Linux kernels all my career and always wondered about lack of sophisticated tools to debug and analyze system-level logs. Always had to resort to manually skimming through large log files to find something I needed to. With the rise of LLMs and the AI-age, I felt it was a great opportunity to build something for OS engineers, which is what led to logcat.ai! We are building the industry-first observability platform for system level intelligence. Think "Datadog for operating systems" instead of applications. Currently, we support…
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Trace, evaluate, and improve AI agents in production
30d ago · telerik.com
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- 4AF
Intellize.ai is a cutting-edge AI-driven observability platform designed to simplify developers' tasks. With our platform, developers can seamlessly search logs, craft dashboards, and configure alerts using natural language. We envision a future where developer tools offer an intuitive and streamlined experience, ensuring users receive precisely what they request. For example, traditional methods of sifting through logs can be cumbersome due to redundant and extraneous data. One way to address this is to ask Intellize.ai to group similar logs, enhancing clarity and efficiency. Our platform…
2023 · intellize.ai
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Hello HN! My name is Max, and I’m a co-founder at Lynx (https://uselynx.ai). We’re building an AI-powered incident resolution platform to help engineers debug and resolve on-call issues faster. If you’ve ever been paged in the middle of the night and had to spend hours piecing together logs, metrics, and code, we’d love your feedback. * The Problem * On-call hasn’t kept pace with modern engineering. Even with great observability tools, diagnosing incidents is slow because: - Systems are increasingly complex. - Logs, dashboards, and documentation are scattered. - Context often…
2025
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2016 · monique.io
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Hi HN, I’m the creator of Cordum. I’ve been working in DevOps and infrastructure for years (currently in the fintech/security space), and as I started playing with AI agents, I noticed a scary pattern. Most "safety" mechanisms rely on system prompts ("Please don't do X") or flimsy Python logic inside the agent itself. If we treat agents as autonomous employees, giving them root access and hoping they listen to instructions felt insane to me. I wanted a way to enforce hard constraints that the LLM cannot override, no matter how "jailbroken" it gets. So I built Cordum. It’s an open-source…
Jan 2026 · github.com
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Hey HN community! Over the past year, AI copilots like Cursor and Windsurf have fueled a dramatic shift in software engineering workflows. And yet, many technical users in adjacent fields like data science and analytics have been unable to reap the rewards of this revolution. It turns out that the existing tools are a poor match for analytical workloads. Beyond that Cursor and similar tools have very poor support for Jupyter notebooks, data science is a fundamentally different discipline from software engineering and we believe it requires a correspondingly different tool. We're excited to…
Sep 2025 · sphinx.ai
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Hey everyone, My friend and I built a simple bug fixing app that listens for alerts/issues from Sentry, contextualizes it against your codebase, and any other data sources you wish to connect (right now we support Notion, Google Docs, and Slack), and deploys an ai agent to write a PR for review in Github or Gitlab to solve the bug. Our current demo shows the end-to-end process for a trivial bug fix, but we have been testing it with open source python repos like http-pie, comparing how our agent solves a bug compared to a human engineer and it gets fairly close. We are working on adding…
2023 · resolvd.ai
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I have a favour to ask. I’ve been working for a while on Kalavai, a project to make distributed AI easy. There are brilliant tools out there to help AI hobbyists and devs on the software layer (shout out to vLLM and llamacpp amongst many others!) but it’s a jungle out there when it comes to procuring and managing the necessary hardware resources and orchestrating them. This has always led me to compromise on the size of the models I end up using (quantized versions, smaller models) to save cost or to play within the limits of my rig. Today I am happy to share the first public version of our…
2024 · github.com
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I’ve been experimenting with infrastructure for multi-agent systems. I built a small project called AgentLog. The core idea is very simple, topics are just append-only JSONL files. Agents publish events over HTTP and subscribe to streams using SSE. The system is intentionally single-node and minimal for now. Future ideas I’m exploring: - replayable agent workflows - tracing reasoning across agents - visualizing event timelines - distributed/federated agent logs Curious if others building agent systems have run into similar needs.
Mar 2026 · github.com
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Hey folks! I'm a founding engineer at Yorph AI, an agentic data platform, built using ADK, that helps users (starting with product managers and analysts) join data from different sources (upload or sync), build version-controlled and reliable data workflows, and clean, analyze, and visualize data — all in one place. We're also releasing semantic layer creation later this week. The beta is live at yorph.ai/login — would love to hear your thoughts and feedback! (FYI: We're still waiting on Google app verification — you'll see a warning for a few days. Dropbox shows a similar one since…
Nov 2025 · yorph.ai
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2024 · iudexai.com
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I'm building out Kerns, as an AI environment for research. You can seed a space with a topic and multiple source documents, and complete your research completely in one space. There's interactive mindmaps for exploration, podcast mode, powerful source readers with original plus chapter level summaries that let you zoom into source on demand, a powerful chat agent that lets you control context and cite refs, and AI assisted note taking. My goal is to have one place to do research on any topic which minimizes manual context engineering, and jumping around between chat/notes/readers.…
Nov 2025 · kerns.ai
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I built this toolkit with my colleague to dive deep into OS internals and automate the identification of privilege escalation vectors. Written in pure C without external dependencies, it explores everything from Linux capabilities and Docker escapes to Windows token manipulation and service permissions. We believe that the constant struggle between breaking and securing systems is the ultimate driver of software evolution. This tool is our contribution to that cycle, designed for researchers who want to understand how low-level misconfigurations can be discovered and audited across different…
Jan 2026
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Hey HN! I just released a suite of AI models for deployment on UAV and other "overhead" devices to provide some understanding of the world below. The objective is to empower all sorts of open-source use cases around search and rescue, wildfire prevention, ground risk mitigation for flight over populated areas etc... The neural networks are trained for a bunch of different devices from big GPUs to tiny edge AI cameras like the Luxonis OAK, with some optimised ones for Nvidia TensorRT and other cool bits and pieces too. The main release package also includes some boilerplate code for running…
2023 · github.com
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Two months ago, my friends in AI and I asked: What if an AI could actually use a phone like a human? So we built an agentic framework that taps, swipes, types… and somehow it’s outperforming giant labs like Google DeepMind and Microsoft Research on the AndroidWorld benchmark. We were thrilled about our results until a massive lab (Zhipu AI) released its results last week to take the top spot. They’re slightly ahead, but they have an army of 50+ phds and I don't see how a team like us can compete with them, that does not seem realistic... except that they're closed source. And we decided to…
2025 · github.com
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TL;DR: we built a framework-agnostic agent runtime that uses gVisor for isolation and runs on k8s. It’s open-source under AGPLv3 Recently we’ve been working on a customer support “AI assistant” - essentially an interactive knowledge base/L1 support but with an option to touch resources that belong to a customer it’s talking to. We found existing tools to be lacking in these aspects: 1. Fully intercepted i/o. We wanted to trace out LLM calls as well as any other networking calls attempted by the harness so that guardrails and audit trails apply to all current and future systems…
Jul 2026 · github.com
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I built an open-source AIOps MCP (Monitoring & Control Plane) that detects anomalies in logs using Isolation Forest. It accepts logs from agents, apps, or collectors, parses and extracts features, and identifies unusual patterns in real time. Alerts can be sent to Slack, Webhooks, or PagerDuty. It’s lightweight, easy to deploy with Kubernetes & Helm, and designed to plug into existing observability stacks. I built this to experiment with combining ML-based anomaly detection and flexible alerting for DevOps/SRE teams. Most AIOps platforms are either too heavyweight or closed-source — I…
2025 · github.com
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A friend and I are launching an alpha first thing in 2011. We're trying to gain some momentum and whatnot, so we're opening early registration as of tonight. We're planning to develop a Bayesian network to derive suggestions. If you're interested in seeing our progress, check it out. Edit: Any and all suggestions, criticism, advice, etc is highly appreciated!
2010 · osmoar.com
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At Laminar (https://github.com/lmnr-ai/lmnr) we're building open source AI observability platform in Rust. We obsess over instrumentation DX for our Python and TS SDKs and in this new blog we outline how we made the most seamless way of instrumenting recently released claude agent sdk
Dec 2025 · laminar.sh
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Hi HN, We’re the team at MyDecisive.ai, and today we’re giving developers a peek at Octant — point-and-click control and visibility for your OpenTelemetry. You've likely felt the pain of the "observability tax," especially if you manage K8S clusters. The modern standard is to instrument everything with OpenTelemetry, but piping all those rich OTLP logs, metrics, and traces straight to a SaaS vendor (Datadog, Splunk, Honeycomb) gets expensive fast. You end up paying massive ingestion and storage costs for noisy, low-value data just so it's searchable when something breaks. With Octant you get…
Jun 2026
- 23WM
We've recently made our product, ozma.io, open-source. It's a CRM/ERP platform for building enterprise systems. We believe that AI will soon handle implementing most of the boilerplate and UIs in the specialized business software. Just look at what lovable.dev does today! Soon products which make creating business software easier for developers will become obsolete, or transform into "libraries" to be used by AIs. We are losing this race, so we go the second route — publish everything and go on building other products on top of it. GitHub repo URL:…
2025 · github.com
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Wanted to share some exciting news - CAST AI (AI-driven cloud cost monitoring and management platform) has launched a free Cloud security insights tool for K8s. Security Insights offers the following features: Kubernetes configuration checks, to ensure your cluster is configured according to best practices for pods and workloads. Users are provided with details on individual checks and resources through CAST AI’s user interface. Vulnerability scans, which offer an overview of potential issues that might appear due to container images downloaded from public registries. Round-the-clock…
2022 · cast.ai
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