Alternatives
Products that do what Margin Ai does
Cut AI token spend by 50% & fix privacy with 1 line of code
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Hey HN: Kaveh here, the founder of https://www.usage.ai/ We help companies drive down AWS EC2 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. Previous to founding Usage, I worked on high-performance computing research at JP Morgan Chase and as a software engineer at a number of smaller startups. Here's how it works: We are typically brought in by a DevOps manager to cut AWS EC2 costs. The app is entirely self-service and the savings are generated automatically,…
2022 · usage.ai
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Hey HN, We’re two developers (co-founders) with a team of 20 who got tired of spending hours reviewing PRs, so we built Infinitcode.ai, an AI-powered code reviewer that: - *Summarizes PRs in plain English*: No more deciphering 1,000-line diff jungles - *Catches more than bugs*: Security holes, performance pitfalls, code smells, even typos (yes, we’ll flag “vurnerabilities” and vulnerabilities) - *Zero onboarding*: Works instantly—no “let me learn your codebase for weeks” nonsense. Why we’re posting: We’re in alpha and need brutal honesty. Roast our tool, mock our UI, or tell us why AI will…
2025 · infinitcode.ai
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Enterprise AIOS Gateway & Semantic Cache to Stop Token Bleed
Jun 2026 · tokenlens.co.in
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Hey HN! I built Retain as the evolution of claude-reflect (github.com/BayramAnnakov/claude-reflect). The original problem: I use Claude Code/Codex daily for coding, plus claude.ai and ChatGPT occasionally. Every conversation contains decisions, corrections, and patterns I forget existed weeks later. I kept re-explaining the same preferences. claude-reflect was a CLI tool that extracted learnings from Claude Code sessions. Retain takes this further with a native macOS app that: - Aggregates conversations from Claude Code, claude.ai, ChatGPT, and Codex CLI - Instant full-text…
Jan 2026 · github.com
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Hi everyone, I've been working on a side project over quarantine called Usage.ai and I finally feel comfortable enough to launch it. We're a service that plugs directly into AWS, automatically finds savings, and applies those savings at the press of a confirmation button all without ever needing to go to an AWS console. I'd love to get HN's thoughts on it! Demo: https://www.loom.com/share/2a6f1c8e4c214914a1cdd88c6fdec4ac Link: https://www.usage.ai/
2020
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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 community! My name is Kane and I'm on the product team at www.usage.ai , a cloud cost optimization company. After honing our product on AWS, I'm excited to announce our availability for customers on GCP and Azure! At a high level, Usage insures committed use-discounts (CUDs) to reduce commitment risk and enable higher savings for companies on the cloud. With traditional CUDs, you commit to a certain level of usage over a specified period in exchange for discounted rates from the cloud provider. However, if your actual usage falls short of the committed amount, you may not fully realize…
2024
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Hello HN! We're building a caching solution for LLMs (ChatGPT, Claude). By combining cutting-edge approaches, such as edge computing, prompt compression, vectorization, and others - it can reduce your AI bills by up to 10x and significantly lower response times. Key Features: - cost efficiency: our system stores frequent queries, reducing the number of upstream (paid) API calls - fast responses: with various nodes globally, we reduce latency by serving data from the nearest location - scalability: designed to handle increasing loads and data sizes without degrading performance. The cache…
2024 · edgematic.dev
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Hey HN, Automated research is the next big step in AI, with companies like OpenAI aiming to debut a fully automated researcher by 2028 (https://www.technologyreview.com/2026/03/20/1134438/openai-i...). However, there is a very real possibility that much of this corporate research will remain closed to the general public. To counter this, we spent the last month building Enlidea---a machine-to-machine ecosystem for open research. It's a decentralized research hub where autonomous agents propose hypotheses, stake bounties, execute code, and perform automated…
Mar 2026 · enlidea.com
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Know your AI agent unit economics.
Jul 2026 · ai-margin-calculator.vercel.app
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Cut LLM costs. Free audit, pay only if it works.
Jun 2026 · decomp-ai.vercel.app
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