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Products that do what Capture the real AI efficiency does
The AI implementation layer for the top 7%
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Professional-grade stock investing, simplified with AI.
Mar 2026 · accountable.finance
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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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Hey HN, I’m the founder of SyncAI. Previously, I was building internal tools for a fintech startup. We tried using GPT-4 Vision and various OCR APIs to automate our Accounts Payable. They worked great for ~90% of documents. The problem was the other 10%: crumpled receipts, handwritten delivery notes, or invoices with weird layouts. In fintech, a 90% success rate isn’t automation; it’s a liability. We spent more time fixing the AI’s hallucinations than if we had just typed it manually. I realized that for high-stakes operations, we didn’t need "better AI"—we needed a Safety Layer. So I built…
Jan 2026 · sync-ai-11fj.vercel.app
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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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I built a web page that aggregates data about data center buildup, sovereign fund investments into AI and bottlenecks. The objective is to predict AI race cooldown by looking at a potential decrease of activity involving these elements. The website looks at the quarterly forms from the 5 biggest hyperscalers and adds their CapEx into the mix, calculating a composite index in the end showing how likely it is for the AI race to slow down. Enjoy!
Jul 2026 · laurentiugabriel.github.io
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Hey HN, we built an Econ+Finance database to let AI agents do investment research. We spend a lot of tokens to organize macro releases and SEC filings into a clean format, so that your agents have more context to do actual analysis. The problem AI agents are great at data analysis. But they become ineffective if most of their context window is spent on gathering and cleaning data, instead of validating hypotheses. Data in the wild is messy and rarely standardized. Definitions and measurements change over time. This problem is compounded by a fragmented data universe. Point solutions exist…
Jul 2026 · github.com
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OP here: this project was born out of the frustration/paranoia that AI providers are throttling their models when their server load is too high. So, I set out to model and study the problem mathematically to understand what was happening, what I found was quite surprising. The idea seems natural: as the data center demand increases momentarily through the day, throttling their models (either using quantized versions, reducing the context window or lowering the tier of the model to a smaller one) seems appealing as the replacement model in principle uses less electricity. The problem is…
9d ago · throttle.staffinganalytics.io
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Most mortgage processing delays aren’t due to risk — they’re due to manual workflows. We’ve been working on SimplAI, an AI-driven system designed for banking and financial services, starting with mortgage operations. The problem we kept seeing: 15–22 day processing timelines Heavy manual document handling (500+ pages per loan) Repetitive data entry + verification loops Underwriters spending hours on non-decision work So we built a set of AI agents that handle the operational layer: Document AI (IDP) → classifies + extracts data from loan docs in minutes Income analysis models → parse tax…
Mar 2026 · app.simplai.ai
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Write contextualized proposals in minutes, not days with AI
Dec 2025
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