Alternatives
Products that do what Glynn does
See all AI spending in one place
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Track your AI spend and connect it to business outcomes
Aug 2026 · rippling.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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I started leaning in on AI heavily this year, as I wanted to get more done autonomously, but then my token usage climbed dramatically to the point where my weekly quota would run out before the end of the week, sometimes a couple of days into the week. I realised I had to do something about it else I'd have to double my spend. So I decided to start tracking my cost per task type. This revealed that a lot of my spend went to searches/scans or simple things like scouting tasks. I then decided to turn this into a simple CLI tool that can be used to read your OpenAI-style logs locally, and…
Jul 2026 · github.com
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Hello HN Viewers, So this all started when we got super frustrated trying to figure out payment fees. You know how it goes – you have got a bunch of payment providers, each with their own fee reports, and trying to make sense of all that mess is quite challenging and complex. We thought, why not just build something that pulls all those fee reports together, cleans them up, and makes them actually understandable? So we built a tool that pulls in fee reports from multiple providers, standardizes fee names, and makes it easier to understand all fee types. You can drill down to see the exact…
2025 · hypersense.io
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Hi HN, we're Kiran and Vijay! Over the past two years, we have built a columnar storage engine for observability: logs, metrics, and traces. Today, it's exciting for us to show what we've built on top of that foundation: LLM Agent Observability. Given how non-deterministic agents are, storing all traces without sampling was critical for us. But these traces tend to be in the MBs, sometimes GBs - we needed to store them inexpensively. We also needed the queries and analyses to be fast. To meet both these goals, we store them in S3 in our own parquet-like file format, and query them using AWS…
Jul 2026 · oodle.ai
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Hello Folks, I am an indie developer, For the last 5 months I was freelancing by building GPT-powered chatbots. One of the challenges I faced was not having visibility into my OpenAI costs. This is why I have built a dashboard to get a complete breakdown of my OpenAI API usage through network calls from OpenAI. Please give it a try & help with feedback on how I can further improve the product,which can really add value and save some money. Note: 1)I found this API through the network logs of the billing screen. 2)The tool stores the OpenAI Key locally on the browser.
2023 · puddl.io
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Hey HN, I kept seeing the same question asked over and over in startup communities: "What tech stack should I use for my SaaS?" The answers were always scattered, opinionated, and never accounted for budget or team size. So I built appstackbuilder.com — you tell it your monthly budget, app type, team size, and skill level, and it recommends a full stack (auth, database, hosting, payments, analytics, etc.) with actual pricing for each tool. A few things that make it different from generic advice: - It accounts for team size when calculating costs (e.g. Clerk charges per user, Linear charges…
Feb 2026 · appstackbuilder.com
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How it works (tech stack): -Built entirely with Lovabl.dev (no-code front-end + logic) -ChatGPT / Claude for research and inspiration -Powered by GPT-4 Vision to interpret charts visually -Hosted on Supabase for performance & caching It’s not meant to replace analysts — just to speed up how traders interpret data. I’m a designer exploring AI tools, and this is my first attempt to turn an idea into a functional product. Would love to know what you think.
Oct 2025 · quantify-ai.co
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Hey HN: Kaveh here, founder of https://www.usage.ai/ We help companies drive down AWS, GCP, and Azure spend. Why? Because the way it's done now is a pain. DevOps and Software Engineers end up spending time managing costs rather than focusing on business problems. I have been building Usage AI for almost 4 years now (4 year anniversary in 1 month from now!) with an incredible group of founding people. We started as a product just to help lower AWS EC2 costs, and now we do all major AWS services (such as RDS, OpenSearch, ElastiCache, and Redshift with more on the way) and other…
2024
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Hi HN, My name is Ben Schaechter and I’m Co-Founder and CEO of https://vantage.sh - a cloud cost visibility and optimization platform. We just added support for monitoring OpenAI costs and usage to Vantage and I wanted to share a demo we put together with HN as I thought people might find it interesting: https://www.youtube.com/watch?v=CzAOU1-uMrM In early April we started getting requests from customers to add OpenAI cost support specifically as it was a bit opaque as to what exactly was driving costs. The way this works is that it uses an undocumented API available…
2023
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