AI · alternatives · 2026
24 alternatives to AI Analytics for Humans
Looking for feedback on how Props can make your life easier as an LLM application developer.
Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. AI Analytics for Humans launched in 2024; newer entries below may have overtaken it.
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Trails▲81Hey all, Justin here. I previously built Phind, the AI search engine for developers. One of the biggest problems we had there was figuring out what went wrong with bad searches. We had tons of searches per day, but less than 1% of users gave any explicit feedback. So we were either manually digging through searches or making general system improvements and hoping they helped. This problem gets harder with agents. Traces are longer and more complex. It takes more effort to review them, so I'm building a tool that lets you analyze LLM outputs directly to help developers of LLM apps and agents…
Jan 2026 · trails-red.vercel.app · its alternatives →
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Ask Viable▲185Transform feedback into PRDs, FAQs, reports & more in mins
2023 · askviable.com · its alternatives →
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Humans vs LLMs▲138Hi HN, We just launched [AI Page Ready](https://aipageready.com) — a tool to check if your web pages are discoverable and understandable by AI tools like ChatGPT, Claude, Gemini, and Perplexity. It runs 40+ checks across six areas: Discoverability & Crawlability, Structured Data & Semantics, Content Quality, Answer-Ready Formatting, Accessibility & Rendering, and Deep AI LLM-specific checks. Would love your feedback — especially if you work in eCommerce, SEO, content, SaaS, or are trying to get traffic from AI tools. (Also open to ideas on what else to add to the tool!)
2025 · aipageready.com · its alternatives →
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A self-improving branded AI FAQ page
7d ago · actuallyasked.com · its alternatives →
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Hey HN, Hakim here from Fini (YC S22), a startup focused on providing automated customer support bots for enterprises that have a high volume of support requests. Today, one of the largest use cases of LLMs is for the purpose of automating support. As the space has evolved over the past year, there has subsequently been a need for evaluations of LLM outputs - and a sea of LLM Evals packages have been released. "LLM evals" refer to the evaluation of large language models, assessing how well these AI systems understand and generate human-like text. These packages have recently relied on…
2024 · github.com · its alternatives →
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UserWatch▲18tldr: it's essentially Cursor but for Product Analytics. AI that sets up your PostHog. Hey, I'm Dima, a former PM who led product redesign and had a constant analytics hangover, and now a solo SF founder who only has time either to ship a new product or recruit users. Analytics is always lagging behind and piling up into an annoying debt. I was also reflecting on product management as a job in general and was thinking about hard skills, and came to a conclusion that analytics is the only hard skill of a PM, and analytics is essentially the coding of the PM. Given the AI and MCP boom, I…
2024 · userwatch.xyz · its alternatives →
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The LLM Evaluation Framework. Contribute to confident-ai/deepeval development by creating an account on GitHub.
2023 · github.com · its alternatives →
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Hey HN, I've been working on something cool that I wanted to share with you all. It's called Viewpoint, an analytics tool for LLMs like OpenAI, Anthropic models, and Gemini. The idea came from the constant flood of new LLM models and the need to figure out which ones work best for my projects without breaking the bank. With viewpoint, I can track token usage, costs, latency(WIP), and traffic over time, making it easier to compare different models and see which ones perform best and save money. The tool works asynchronously, so it doesn't add any latency to your LLM requests, and you have…
2024 · viewpointhq.com · its alternatives →
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Hey all! @sridatta and I wrote a book/zine called Forest Friends on system evals for LLM-driven apps. But it's a bit more whimsical, a bit more visual, and very much inspired by the meme of LLMs being a shoggoth polished into a smiley face with RLHF. LLM system evals are important as companies move past the flashy AI demos to reliable production apps. System evals keep coming up as the answer for what you "should do", but it's not exactly a standard part of the software engineering toolkit. So we pulled from @sridatta's seven years as a research engineer at Google, plus a ton of best…
2024 · its alternatives →
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I found myself building a bunch of LLM-backed features that needed to use tool calling, and some of those tools involved doing things that were somewhat high stakes - communicating on my behalf or modifying shared / production data. one example - I wanted to replace a marketing website with a chatbot + vector DB loaded with the previous content, docs, and blog posts. Between hallucinations, missing knowledge base info, and the LLM generally writing like an psuedo-intellectual high schooler, I realized I couldn't trust it to communicate unsupervised with my website visitors. I needed a…
2024 · github.com · its alternatives →
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RagMetrics▲13We built live AI evaluation to detect hallucinations, grounding issues, and drift as outputs are generated. This helps teams move GenAI from pilots into production.
2025 · ragmetrics.ai · its alternatives →
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At testup.io we have been working for a while to bring artificial intelligence to the field of test automation. Just a few years ago, the primary challenge laid in accurately identifying UI elements following minor structural changes, such as updates to IDs or paths. The emergence of Large Language Models (LLMs) raised the bar for what it meant to be smart. Now, we anticipate the robot to do lots of things autonomously, such as retry in cases of unresponsiveness or handle minor error reports. A more challenging, but soon expected feature, would involve the test robot navigating your web shop…
2024 · github.com · its alternatives →
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I’ve been building LLM tooling for a small VC fund and found myself explaining the same mental model over and over to non-technical people around me: how a stateless LLM becomes a chatbot, how tool use works, what an agent is mechanically, and why context windows shape all of it. I never found a guide that covered that full chain at the level I wanted, so I wrote one. It’s nine short chapters, each building on the last. Deliberately simplified: the goal is a useful mental model, not a textbook. Feedback, corrections, and contributions welcome: github.com/ymyke/aiaiai
Apr 2026 · aiaiai.guide · its alternatives →
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Hey HN! When I started looking into LLMs and agents for software development and introducing them at work, I quickly realised that a person new to the topic faces a real barrage: - all the hype (AGI, engineers getting replaced by AI etc.) - conflicting opinions in virtually every discussion—for every person saying they’ve 10x-ed their productivity, there is a comment decrying LLMs as an utter failure - a lot of jargon (MoE, MCP, RAG, distillation, quantisation etc. etc.) - a profusion of models, IDEs/IDE extensions, CLI agents, other tools etc. Sorting through all of this can be quite…
2025 · nohypeai.dev · its alternatives →
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Hi HN. I heard you like dev tools and AI, so we wanted to share our project that we’ve been working on. We’re working on Horizon [1] - a higher level abstraction for LLMs so that developers can spend less time trying to grapple with LLMs to make them work and more time with users. This is the starting feature set which takes an auto-ML approach to identify the optimal LLM model, hyperparameters, and prompt - instead of just giving you the tooling to figure it out yourself. You can read more about it in our documentations. Our view is that as LLMs become increasingly commoditized and prompts…
2023 · gethorizon.ai · its alternatives →
- 21IB
I built a tool to roast landing pages with AI agents. I was gathering feedback from watching landing page roast videos, and figured out I could prompt LLMs to analyse a screenshot and roast based on the same criteria. It's not 100% accurate yet, but it has been really insightful when I've tested it on my own websites. Let me know what you think!
2024 · roastmylandingpage.io · its alternatives →
- 22IE
Hi HN! I spent the last year traveling and feeling purposeless after shutting down my last startup (Zage YC S’21) in Dec 2022. There were some obstacles I couldn’t overcome and decided to return investors 50% of their capital. To afford (and justify to myself) traveling, I started consulting as an engineer and product designer. I started (https://backspace.nyc) and it was a good time. I (and some friends) built a handful of AI experiences and learned a lot along the way. The hardest thing about running a services business shipping and selling AI experiences powered by LLMs was…
2024 · loom.com · its alternatives →
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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 · its alternatives →
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I've been experimenting with ways to increase AI adoption for non-technical people. Basically, all companies are pushing for AI because it's all over the news and they feel left behind but most people have no clue where to start. I think 90% of people (ie non coders) are sufficiently well served by using cowork instead of claude code or something similar. If we can get people from sales, customer support, marketing, etc to collaborate with skills and cowork to form a company brain, I think it's gold. So I think there's opportunity for the community to share skills that work well for 1000s of…
Jun 2026 · claudinho.xyz · its alternatives →
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