Dev tools · alternatives · 2026
24 alternatives to Openlayer – Test, fix, and improve your ML models
Hey HN, my name is Vikas, and my cofounders Rish, Gabe and I are building Openlayer: http://openlayer.com/ Openlayer is an ML testing, evaluation, and observability platform designed to help teams pinpoint and resolve issues in their models. We were ML engineers experiencing the struggle that goes into properly evaluating models, making them robust to the myriad of unexpected edge cases they encounter in production, and understanding the reasons behind their mistakes. It was like playing an endless game of whack-a-mole with Jupyter notebooks and CSV files — fix one issue and…
Openlayer is a platform for testing, evaluating, and monitoring machine learning models in production. It helps ML teams identify and fix issues like unexpected edge cases and model errors that traditional software… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Openlayer – Test, fix, and improve your ML models launched in 2023; newer entries below may have overtaken it.
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OpenSEO▲928Hello! For the last 2 months, I've been building OpenSEO. It's a user friendly UI wrapping the DataForSEO API which has high quality SEO data for keywords, backlinks, AI SEO and competitor research. Instead of paying $100+ per month, you buy DataForSEO credits and pay only for usage. The coolest thing about the project so far has been hearing about what people are building on top of it. People are using coding agents to quickly integrate with Google Search Console, Google Ads and building their own AI SEO and reporting features. Many were already building their own custom solutions around…
Jul 2026 · openseo.so · its alternatives →
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Open source tool for testing & validating your model & data
2022 · github.com · its alternatives →
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TensorZero▲307Hi 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:…
2025 · github.com · its alternatives →
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OpenTelemetry-native observability for agents and LLMs
Aug 2026 · openobserve.ai · its alternatives →
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Hey HN, We just recently launched Forge – an AI model API platform that lets you access and call AI models from multiple providers in one place. Find it on our website: https://tensorblock.co/forge Some key features: Unified API Key – Store multiple provider API keys and access all with a single Forge API key. OpenAI API Compatible – Drop-in replacement for any application that uses OpenAI’s API. Advanced Security – Strong Encryption for API keys with JWT-based authentication. Client Management – Easy key and user management via included command-line interface. Open-source –…
2025 · tensorblock.co · its alternatives →
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oqoqo▲325Most benchmarks today exist in curated environments and do not translate well to the real world. We built Oqoqo to bridge this gap. Oqoqo makes it super simple to build realistic evals and custom benchmarks for tasks users actually care about. Oqoqo can: - Reliably measure how agent friendly your product surfaces are against Codex, Claude Code, OpenClaw, Hermes, Pi, Opencode, Cursor, GitHub Copilot - Regression test MCP, CLI, skills, SDK, and any agent facing interface (we are continuously using Oqoqo to dogfood and improve our own MCP/CLI) - Create and share custom benchmarks for how…
Aug 2026 · oqoqo.ai · its alternatives →
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Hi HN, we built an open source model gateway. It's a single place to manage our own self hosted, frontier, and open source models in one place. It’s is rust native, built for concurrency, and implements all the config quirks across models and providers (streaming formats, tool calls, model parameters, rate limits, and different error behavior). The gateway adds under 1 ms for BYOK requests and under 2 ms when Experiential supplies the provider key. It has every major inference provider, and 1000+ models refreshed daily via a codex agent that opens a PR. Compared to other similar projects…
Aug 2026 · github.com · its alternatives →
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Hey HN. We’re Jay and Vadim from Highlight.io (https://highlight.io). We’re building an open source [1] monitoring platform for web applications. Today we’re excited to be sharing a performance tool we’ve been working on, which helps you inspect the latency of code execution from the client to the server. As engineers at past startups, we often had to debug slow queries, poor load times, inconsistent errors, etc... While tools like Jaegar [2] helped us inspect server-side performance, we had no way to tie user events to the traces we were inspecting. In other words, although we had…
2024 · github.com · its alternatives →
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Hey! My name is Dima, I am from Ukraine and I am the co-founder of Lost Pixel! We built this tool to solve our problems at work and decided to open-source it so more people can build their custom visual regression testing pipelines! If you want to chat about the tool or visual regression testing in general I am super excited to meet like-minded people! Thanks a lot for checking out the product and I hope it will serve you well if you decide to try it out :D
2022 · github.com · its alternatives →
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Production infrastructure for machine learning at scale - cortexlabs/cortex
2019 · github.com · its alternatives →
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Hi! One of the creators here. Very proud to finally be able to show you what we've been working on for over a year now. Curious to hear your thoughts! Objectiv is open-source (APLv2) product analytics infrastructure. It's built around a generic but strict event taxonomy, open/common data- and infra tools (currently PG, snowplow, working on bigquery with more to come), and the analyses are done using our pandas-like, SQL speaking modeling library called Bach. As a result, we’re moving towards a vision wherein models can be shared openly, independent of product, platform[1] or data…
2022 · objectiv.io · its alternatives →
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FiftyOne▲75Accelerate your machine learning experimentation
2020 · docs.voxel51.com · its alternatives →
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Hi Hacker News! We’re Vadim and Chris from Highlight.io [1]. We do web app monitoring and are working on using LLMs/embeddings to add new functionality to our error monitoring product. Given that there’s a lot of founders/engineers using LLMs in their products, we figured we’d share how we built the new functionality, their impact on our workflows, and how you can try it out. Our goal was to build two features: (1) tagging errors (e.g. deeming an error as “authentication error” or a “database error”); and (2) grouping similar errors together (e.g. two errors that have a different…
2023 · github.com · its alternatives →
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OrchestraML▲82From English prompt to deployed ML model with human approval
Jun 2026 · orchestra-ml.vercel.app · its alternatives →
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Easy to integrate and reliable visual regression testing cloud. Sleep better at night while shipping features.
2023 · lost-pixel.com · its alternatives →
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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →