Partner Success with AWS / Digital Marketing / Israel
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How Anodot and Automat-it Cut 30% from AI Classification Using Amazon Bedrock
Find out how Anodot accelerated a key part of its natural language FinOps tool by 30 percent by migrating to Amazon Bedrock with Automat-it.
30%
better performance of classification agent
Zero
increase in costs
Zero
decrease in accuracy
Overview
Israel-based Anodot provides AI-powered FinOps for its customers to allow them to track and measure their use of cloud services. Its CostGPT product lets users interrogate spending on cloud services using natural language queries. The first stage of its AI process is to classify questions asked according to six categories, but CostGPT customer experience was being impacted by slow categorization. Anodot worked with AWS Partner Automat-it to migrate its workloads to Amazon Web Services (AWS). The move increased the speed of its classification engine by 30 percent.
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Opportunity | Improving Performance of Natural-Language FinOps System
FinOps specialist Anodot offers a range of services for its customers to help them understand and better control their cloud spending. Most of its services rely on dashboards to interrogate and understand cloud use and spending. It has worked closely with Automat-it for some years as a partner and provider of services—and a majority of Automat-it’s customers now use Anodot products.
Anodot’s CostGPT product aims to provide advanced FinOps clients with a deeper understanding of their cloud spend beyond the simple dashboards. The software uses a large language model (LLM) to answer natural-language queries posed by the customer. When the user first poses a question to CostGPT, the system must first classify the query into one of six possible categories. This helps it to provide an accurate answer by selecting the correct model. These categories include informing the system whether it needs to consult historic spending data, predict or forecast future spending, or create an answer in a graphic or visual format. Depending on the category, CostGPT then knows which algorithms to use to find an answer.
The system worked well and provided accurate answers but there was an issue with latency. Some queries were taking 10–15 seconds to generate a response, which was frustrating for customers. After an investigation, Anodot concluded there was a frequent issue with the speed of classification of questions rather than just a network issue. Anodot and Automat-it considered how they might solve this problem—either by reducing network issues by being closer to customers or by running models more quickly on AWS.
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Our combined expertise in cost management and Amazon Bedrock helped Anodot bypass weeks of setup and experimentation time, saving money and driving productivity.”
Ziv Kashtan
Chief Executive Officer at Automat-it
Solution | Running in Hours, Production in 2 Days
Anodot already hosts most of its services on AWS and had considered experimenting with Amazon Bedrock to build and scale generative AI applications with foundation models. It had delayed doing so because it was worried it would take a long time to set up and produce meaningful results. Anodot assumed that building a proof of concept would be expensive and absorb DevOps and management time—all with no guarantee of any benefits at the end.
“We thought the learning curve would be steep, and it would take 2-3 weeks to learn how to set it up,” says Ira Cohen, chief data scientist at Anodot. “But Automat-it had us up and running on Bedrock in a matter of hours—and fully working in 2 days.” It uses natural language processing (NLP), which means customers get answers more quickly and can engage with the service in a more natural way. “Amazon Bedrock gives us the flexibility of using various different models,” says Cohen. “And we can do that without having to learn a whole new interface.”
Anodot discovered that Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models from leading AI companies through a single API along with a broad set of capabilities that allows the building of generative AI applications with security, privacy, and responsible AI. Anodot also chose to use Amazon Bedrock to support the wider development of CostGPT. It wanted to speed up customers’ ability to learn about its services and speed up how fast Anodot learns about its customers from the questions they asked. Automat-it configured Bedrock to identify areas where customers were not fully informed about services. This would allow Anodot to adjust its marketing messages. It can also highlight gaps in the rest of its portfolio. For example, if lots of customers are asking CostGPT the same question then maybe that data should be added to the dashboards.
Outcome | Deeper Understanding of Customers and 30% Performance Increase
Migrating CostGPT to AWS resulted in a zero decrease in accuracy and in some cases Anodot reported improvements. In addition, there has been zero increase in operating costs. However, the queries are now delivered 30 percent faster compared to the previous LLM. As well as accelerating the categorization engine, the tool is now configured to collect usage data as well as the kinds of questions customers were asking to support product development. “Working with Anodot was a perfect example of how our combined expertise in cost management and Amazon Bedrock helped them bypass weeks of setup and experimentation time, saving money and driving productivity,” says Ziv Kashtan, chief executive officer at Automat-it. “We rapidly had their system up and running, allowing them to focus on what matters most. We're proud to be part of their journey and continue collaborating with them, to help other tech startups reduce their cloud costs."
CostGPT is also seeing widening use of FinOps tools by its customers. Because of the ease of use of its natural-language interface, it is used more widely than just within the FinOps team. Chief executives, non-FinOps finance, researchers, and development staff are all using it to dig down into an organization’s spending on cloud without needing to know how to use complex systems. Since Amazon Bedrock is an AWS service, Anodot believes this will give its customers a better perception of built-in security. This is important because at some point the company would like to feed customer data back into the system, so its needs to assure customers that their data will be secure.
About Andot
Israel-based Anodot is an AI-based cost management platform that detects waste, tracks savings, and provides transparency on current and future costs, allowing customers to facilitate strategic financial planning and management of multi-cloud environments. It has headquarters in Israel and the US and 70 staff worldwide.
About AWS Partner Automat-it
Established in 2012, Automat-it is an all-in AWS Premier partner empowering startups with DevOps and FinOps expertise and hands-on services. It has guided and supported hundreds of startups in the smarter use of AWS throughout their growth journeys. DevOps born and bred, Automat-it builds cloud solutions from the DevOps perspective for practical applications with built-in efficiencies that save its customers significant time to market and optimize their cloud performance and cloud economics.
AWS Services Used
Amazon Bedrock
Amazon Bedrock is a fully managed service that provides a single API to access and utilize various high-performing foundation models (FMs) from leading AI companies. It offers a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI practices.
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Israel-based Anodot provides AI-powered FinOps for its customers to allow them to track and measure their use of cloud services. Its CostGPT product lets users interrogate spending on cloud services using natural language queries. The first stage of its AI process is to classify questions asked according to six categories, but CostGPT customer experience was being impacted by slow categorization. Anodot worked with AWS Partner Automat-it to migrate its workloads to Amazon Web Services (AWS). The move increased the speed of its classification engine by 30 percent.
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