The use case: how Robinhood deploys AWS Bedrock
Robinhood built a FinCrimes Agent that uses LLMs running on Amazon Bedrock, including Anthropic's Claude Haiku and Sonnet and DeepSeek, to synthesize customer and transactional data into investigative summaries for financial crimes analysts. Each output is checked by validation agents and reviewed by a human investigator.
More reported results
Figures published in AWS Bedrock’s case study. They are not independently measured by usedby.
In just six months, the company scaled from 500 million to 5 billion tokens daily while cutting AI costs by 80% and reducing development time by half.
In the customer’s words
Using Amazon Bedrock, we feel comfortable knowing that the data isn’t leaving our control.Other AI tools used by Robinhood
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Other companies using AWS Bedrock
Customers across industries, with public evidence.
AdobeConfirmed
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Cox AutomotiveConfirmedGo straight to the source
Based on AWS Bedrock’s published case study. We check the public evidence; the results are reported by the vendor.
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- Oct 24, 2026
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With the FinCrimes Agent, Robinhood has achieved roughly a 20 percent cumulative efficiency gain in its investigative workflows. By delivering consistent, high-quality outputs, the solution has significantly reduced the time spent collecting and summarizing data.