Alternatives
Products that do what Google Reviews Analyzer does
Open source Google Reviews analyzer project using LLM
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Hi hacker news, My name is Dillion and I'm the creator of llm.report. A few months ago, I was frustrated by the lack of observability into the OpenAI API. All of us are left in the dark about API performance, latency, cost calculation, cost breakdown, and more. I just wanted to know more about how my AI app is performing in production and make data-driven decisions to improve the product. So I ended up just building it myself. There are three parts to the platform: 1. OpenAI API Dashboard (no-code) - Enter your OpenAI key and get access to detailed insights straight from the OpenAI API…
2023 · github.com
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I’ve spent the last 2.5 months building a product that runs LLM-powered code reviews on my pull requests — and I just launched it. The tool is built specifically for solo developers. You install it on your repo, trigger a scan by creating a pull request, and it leaves structured review comments using OpenAI under the hood. Funnily enough, I used the dev version of this app to review its own pull requests while building it. It helped me spot bugs, simplify structure, and keep quality high — all with minimal need for another human in the loop. Things I want to try out in the next months : -…
2025 · codii.dev
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I was overspending on GPT-4o. It was really hard to compare different models I could switch to, so I built this LLM comparison tool. It shows leaderboards, pricing, and performance data across 100+ LLMs (including all major providers and open-source models). Key features: - Live pricing comparisons - Benchmark Scores (MMLU, HumanEval, GPQA, etc.) - Context length vs cost analysis - Speed/throughput tests across providers - Quality vs price visualizations - Open source (all data verifiable) Try it out: https://llmstats.com I'd like to know your opinion :) Tech stack: Next.js,…
2025 · llm-stats.com
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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
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I built TraceAIO, an open-source tool that prompts LLMs on your behalf and tells you whether ChatGPT, Perplexity, and Gemini mention your brand — and which competitors and sources show up instead. Yeah, this category smells a bit like a grift, same as early SEO. And I think over time it will become just SEO again, and become about good content. The tool just helps you monitor over time. It queries the browser products through real browser sessions, not APIs, runs on Docker, with an MCP server so you can query your own data through an LLM. No business model, Apache 2.0, self hosted. If you…
Jun 2026 · traceaio.org
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It’s just the back end so it logs to MongoDB database so you can add any UI you want to it, feel free to contribute! (Suggestion’?)
2022 · github.com
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2015 · mixedanalytics.com
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Hey HN, Over the last year, I’ve reviewed more than 1000 code changes. Most of the time was spent catching obvious mistakes rather than debating complex design decisions. If we estimate ~10 minutes per review, that’s 160+ hours spent reviewing code in just one year. So I thought: could I get some of that time back using LLMs? That's why I spent the last few weekends building Presubmit.ai, an open-source AI reviewer that runs as a Github Action right when you open a Pull Request. The results so far are promising: I estimate it can reduce the review time by 50%, which in my case would mean I…
2024 · github.com
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Live demo here: http://fonctionlabs.com:8000 Similarly to aka_sh (guess we were working parallelly on similar topics), I created with my brother a chainlit-based webapp, which summarizes Youtube videos in order to gain time. It works as an RAG-based LLM, and is very light in the sense that it does not use RAG libraries like langchain or llamaindex. You can use it with your own OpenAI API key. It also supports local models like Mistral, or Llamma. It is ofc open-source, and you can deploy with Docker if you choose. Some of the next steps are: - using whisper to be able to compute a…
2024 · github.com
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Hello! I built this to solve a personal problem of where I didn't want to wade down large chains of HackerNews comment threads in order to get the key takeaways from the discussions. I built this Chrome extension, which supports both OpenAI and Ollama(local LLMs) to summarize comments and display the summary within Chrome's sidepanel. It's open source as you can see from the link, feedback appreciated!
2024 · github.com
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A few months ago I was working on a flight search engine that would include pet transport costs (I know a few by hearth but storing them and make the calculations in the UI would be nice) While I was collecting pet pricing from several airlines I strugled to extract data in a common format without hallucinated values. That's when I thought: What if I use multiple LLMs and take the most common response to improve accuracy? This idea became this new project. You provide your documents, an SQLModel schema, an LLM provider, plus what you'd like to extract and Extrai does the rest. Including…
Nov 2025 · github.com
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Hi HN, A few weeks ago, we stealth launched SEC Insights on Product Hunt and were thrilled to reach the top 5! What is SEC Insights? It harnesses the Retrieval Augmented Generation (RAG) capabilities of LlamaIndex to provide answers about SEC 10-K & 10-Q documents. The enthusiastic reception we received on Product Hunt prompted us to open-source our project. Now, developers can use our project either as a reference or they can fork it entirely for their LLM-powered applications. We at LlamaIndex built this to help developers move their LLM app ideas from prototype to production. We're very…
2023 · github.com
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This year I’ve reviewed more than 1000 code changes. Most of the time was spent catching obvious mistakes rather than debating complex design decisions. If we estimate ~10 minutes per review, that’s 160+ hours spent reviewing code in just one year. So I thought: could I get some of that time back using LLMs? That's why I spent the last few weekends building an LLM-based prereviewer that should take a first pass before the actual human reviewer. The results so far are promising: I estimate it can reduce the review time by 50%, which in my case would mean I save 80hours (~10 working days) per…
2024 · github.com
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LLM observability is an absolute must-have for anyone running something in prod (or prod-like). While all the observability startups are great, you're essentially sending all your OpenAI usage history - prompts, generations, chats - to a random third party. So this script deploys a basic proxy in your Azure account, catches all incoming OpenAI requests, stores logs in your own resource group, and comes with visualizations premade (charts, timelines, chat history, cost estimation, etc). Thanks for any thoughts and feedback!
2023 · github.com
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We created LightFeed to transform any websites into lightweight and focused news feed. Use LLM to sort and summarize posts using user's custom prompt. For example, you can get anything related to "Games, science or open source" on HN. The news feed is automated daily and you can receive it in browser, email or RSS. We will also open source the LLM web parser/sort library soon o (https://github.com/lightfeed/lightfeed). It reads HTML, turns main content into markdown, uses LLM to parse it into structured feed in JSON, then sort with embedding on user query. It is…
2024 · lightfeed.ai
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