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kaveh@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 clouds: Azure and Google Cloud.
Here's how it works: We are typically brought in by a DevOps manager to cut AWS/GCP/Azure costs. The app is entirely self-service and the savings are generated automatically, typically we do this live on a call. On average, we reduce Cloud spend by 30-50%.
To reduce by 30-50%, we don't touch the instances, require any code change, or change the performance of your instances. We buy Reserved Instances and Savings Plans on your behalf (a billing layer change only) and bundle them with guaranteed buyback. So you get the steep 50% savings of 3-year no-upfront SPs with none of the commitment (we reimburse you for any underutilization).
We make money off of a % Savings Fee. Happy to chat directly kaveh@usage.ai
Have you experienced any issues with managing your company or organization's AWS expenses? We'd love to hear your feedback and ideas!
My name is Kaveh, I'm the founder and CEO of www.usage.ai
I launched on HN last year with the first version of Usage AI, we used Standard RIs and the RI marketplace to give customers the ability to buy 3-year no-upfront RIs which yielded 57% savings with none of the commitment.
In conjunction with AWS, we have since moved to using Convertible Reserved Instances which are the most misunderstood but powerful savings instrument on AWS. As long as you have servers in any of the popular AWS regions, you can achieve up to 50% savings with no code change and the flexibility to scale your workloads up and down using Usage.AI's CRI automation. We blend CRIs with SRIs (that are non-discounted since they can still be traded) and CSPs to maximize a customer's savings rate net of our fees. This is what we call AWS Savings CoPilot.
This has especially helped us assist some of the largest AWS customers with their spend since the volume of RIs can be adjusted up and down in real time at scale.
In addition, for anyone who signs up for Usage.AI Savings CoPilot, we are also including ClearCost, a multi-cloud visibility, budgeting, and anomaly detection tool for AWS, GCP, Azure, Snowflake, Databricks, Datadog, and Kubernetes.
Pricing: You get all of this for a % of what we save you on your AWS bill. Unlike other providers, we do not charge a % of spend.
Are you tasked with managing your AWS bill at your organization? Let me know what you think! You can also reach me directly at kaveh@usage.ai
We just launched a free tool that helps you compare EC2 prices. It's simple and straightforward for now, but I would love the community's thoughts on how we can make it better (or if AWS's pricing page is already good enough).
It requires no log-in or sign-up. You can access it directly here:
https://ec2pricing.usage.ai/
Feel free to ping me directly with feedback: kaveh@usage.ai
We launched on Hacker News for the first time early last year, and we've made a lot of progress since then. We've saved tens of millions of dollars for companies, and we are even more excited to announce the launch of a new product: insured reservations for RDS! We worked closely with AWS on this feature and are excited to finally make it generally available.
We help companies drive down AWS EC2 & RDS spend. Why? Because the way it's done now is a pain. DevOps and Software Engineers end up spending time managing costs and reservations rather than focusing on business problems.
In the early days, we saw horror stories of customers with millions of dollars in monthly on-demand spend simply because their finance team didn't want them committing to AWS. Worst yet, we've seen AWS users who ended up overspending by hundreds of thousands of dollars a month because they overcommitted their Savings Plan commitment.
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, typically we do this live on a call. On average, we reduce AWS EC2 spend by 50% for 5 minutes of work, and RDS spend by ~30%.
To reduce by 50%+, we don't touch the instances, require any code change, or change the performance of your instances. We buy Reserved Instances on your behalf (a billing layer change only) and bundle them with guaranteed buyback. So you get the steep 57% savings of 3-year no-upfront RIs with none of the commitment.
We make money off of a 20% Savings Fee. Happy to chat directly kaveh@usage.ai
Have you experienced any issues with managing your company or organization's AWS expenses? We'd love to hear your feedback and ideas!
We help companies drive down AWS EC2 spend by buying and selling 3-year no-upfront reserved instances. Why? Because there's almost no liquidity on the AWS EC2 RI Marketplace and it can take a while, if at all, to sell an RI if you need to stop using one.
Previous to founding Usage, I worked at JPMorgan Chase as a summer analyst.
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, typically we do this live on a call. On average, we reduce AWS EC2 spend by 50% for 5 minutes of work.
To reduce by 50%+, we've built a pool of reserved instances that's shared across our pool of customers. When a customer scales up their EC2s, Usage buys RIs. When a customer scales down their EC2s, Usage sells RIs. At this point, we've saved companies tens of millions of dollars in spend and have a lot of liquidity, so we take on very little risk.
We make money off of a 20% Savings Fee. Happy to chat directly kaveh@usage.ai
Have you experienced any issues with managing your company or organization's AWS expenses? We'd love to hear your feedback and ideas!
The best part is that we only make money when we help people save; no hidden fees, no long contracts, and hopefully no large bills. Users pay a percentage of savings, billed monthly, and can stop using us whenever they would like. We became profitable 6 months after launch.
But, despite product market fit like I’d never seen (everyone likes to save, especially on their AWS bills), we didn’t take off immediately. Once I’d onboarded my friends from the hackathon circuit, I needed to find a way to bring Usage to a larger audience. I started out placing ads on Google, LinkedIn, and Reddit and was getting a lot of clicks. We were getting 5,000 site visits a month, but conversions were lower than expected. It wasn’t working like I’d hoped.
As a technical founder I had a problem: I knew that the tool I’d built would save companies around 60% on their AWS bills, I just didn’t know how to get in front of the right audience.
That’s when I made what was one of my best decisions: to hire my first salesperson. My advisors told me not to hire him, he was a 22 yr old recent grad working as a forklift driver with no sales experience, but I went ahead anyways. Both of us started cold calling and emailing prospects every morning. After two and a half weeks, we had our first client from cold outreach. We started A/B testing our messaging, trying different approaches and things started taking off. After about a month, we were bringing in around 2 new clients a week.
That’s when we stumbled into our second acquisition channel: partnerships. We were approached by a DevOps shop who had dozens of customers and wanted to white label our solution. I spent the next weeks working around the clock to build out a partner dashboard and API solution. When we integrated, we gained 15 new customers in a week with a total of $2m in AWS spend under management. Pretty soon, we were able to replicate this channel with other DevOps firms and AWS consultancies.
Both partnerships and sales took off and soon we were maxxed out making sure we could onboard customers without our tool breaking. That’s when we decided to double down on both channels. I hired several new sales and partnerships people. While there was a steep learning curve for them to master the AWS jargon and world of cloud compute our pipeline started to fill up. Today, we have over $12m of deals in pipeline and I’m excited to see where things go in 2023.
Looking back, there was no single thing but a lot of small things done right over a year that helped us get to where we are.
https://www.usage.ai/
One of the most significant risks of using ChatGPT is the potential for job losses and a decline in the demand for software engineering skills. As ChatGPT automates many of the tasks traditionally performed by software engineers, there is a real danger that organizations will rely more heavily on this tool and less on human engineers. This could lead to a reduction in the number of software engineering jobs and a decrease in the value of these skills in the market.
Another risk of using ChatGPT is the potential for security and reliability issues. If ChatGPT generates incorrect code or makes mistakes, the consequences could be severe, potentially leading to system failures and data loss. This could have disastrous consequences for organizations and their customers, and highlight the importance of carefully managing the use of ChatGPT in critical systems.
Overall, while ChatGPT has the potential to greatly improve the efficiency of software development, it's important to carefully weigh the potential risks and benefits before adopting this tool. By taking a cautious and measured approach to the use of ChatGPT, organizations can ensure that they are able to reap the benefits of this powerful tool without exposing themselves to unnecessary risks.
Thoughts? Could ChatGPT one day become intelligent enough to replace human software engineers?