AWSPublic SectorEnterprise Knowledge SearchSystem MigrationAI and Machine LearningCloud MigrationCost OptimizationERP / CRMGenerative AI / LLMMedia and ContentCost ReductionProductivity ImprovementScalabilitySpeed to Market2024AWSAWS#ff9900Public SectorGlobalRead AI has been rapidly delivering new features that customers want—for example, custom integrations with business applications including Google Meet, Zoom, Slack, Microsoft Teams, Salesforce, Hubspot, Gmail, Outlook,…Around 30 percent of Read AI’s customers are outside the United States, particularly in Africa and South America.Dec 17, 20246Enterprise Knowledge Search|System MigrationAWS Graviton · Amazon EC202024-12-176
Read AI has been rapidly delivering new features that customers want—for example, custom integrations with business applications including Google Meet, Zoom, Slack, Microsoft Teams, Salesforce, Hubspot, Gmail, Outlook, Jira, Confluence, and others.
↗Around 30 percent of Read AI’s customers are outside the United States, particularly in Africa and South America.
↗As a result, Read AI reduced infrastructure costs by 20 percent, improved performance, and sped up time to market.
↗As of October 2024, Read experienced over 700 percent growth in active users, and it runs 89 percent of its CPU workloads, which constitute 41 percent of its total workloads, on Graviton instances.
↗The company plans to move all compatible CPU workloads to Graviton instances. “When we migrated the services to Graviton instances, there was no tuning necessary and nothing additional required, and we immediately saw a 20 percent reduction of infrastructure costs,” says Williams.
Reported impact
Business outcome
Read AI is currently adopting AWS Graviton4 instances for additional performance benefits. “We want to be on the preview list for every release of Graviton instances so that we can evaluate them as soon as possible,” says Williams. “Using Graviton instances means that we are comfortable being more diverse in our experiments, so engineers can spin up additional resources to run even small experiments, which makes us very nimble going forward.” In October 2024, the company introduced a bundle of new features, including an iOS application for real-world meetings and a Chrome extension—Read AI for Gmail—that brings AI to users’ inboxes. The company is also expanding its generative AI–powered experiences. “Using Graviton instances, we can ship diverse features with a quick turnaround, even with a small team,” says Williams. AWS Graviton–based instances were cost-effective, and the available cores provided the capacity we needed to deliver an AI copilot wherever you work.
Cost Reduction
Productivity Improvement
Scalability
Speed to Market
Solution
Read AI needed to keep up with explosive global growth, including recognition as the sixth fastest-growing AI vendor in the world. As a startup in the field of productivity tools powered by artificial intelligence (AI), Read AI’s competitive edge comes in part from how simply it integrates with various collaboration tools—facilitating its “copilot everywhere” solutions—and from its ability to deliver new features ahead of competitors. In 2024, Read AI adopted AWS Graviton–based Amazon EC2 instances , which are powered by custom-designed AWS Graviton server processors. AWS Graviton–based instances were cost-effective, and the available cores provided the capacity we needed to deliver an AI copilot wherever you work. Learn how productivity AI company Read AI widely delivers copilot capability, reducing costs while boosting performance using AWS Graviton instances. The company was founded on Amazon Web Services (AWS), running compute using Amazon
Data flow
processing runs on Amazon EC2, AWS Graviton for the knowledge search workload.
Solution architecture
2 components · 1 layer
Compute
Amazon EC2Runs core compute or model execution for the knowledge search workload.
AWS GravitonRuns core compute or model execution for the knowledge search workload.
Evidence from the source
As of October 2024, Read experienced over 700 percent growth in active users, and it runs 89 percent of its CPU workloads, which constitute 41 percent of its total workloads, on Graviton instances.
In addition, Read AI boosted performance using Graviton instances. “Reliably across the board, we achieved performance gains on Graviton instances compared with the x86 counterparts, and we also saw significantly greater flexibility than what we could get with our GPU fleet,” says Williams. “They have a lower sticker price, and we can get more done in each unit of time as well.
Read AI began migrating to Graviton instances in December 2023.
Read AI has been rapidly delivering new features that customers want—for example, custom integrations with business applications including Google Meet, Zoom, Slack, Microsoft Teams, Salesforce, Hubspot, Gmail, Outlook, Jira, Confluence, and others.
The company plans to move all compatible CPU workloads to Graviton instances. “When we migrated the services to Graviton instances, there was no tuning necessary and nothing additional required, and we immediately saw a 20 percent reduction of infrastructure costs,” says Williams.
There was no reason not to migrate to Graviton instances.” With the flexibility and the performance boost of using Graviton instances, Read AI increases its speed to market for new features.
Review how this reference was scored and trace each normalized claim back to its documented source.
01
Scoring methodology
How scores are calculated
Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.
Customer reference value85/100
Problem clarity20/20
Measures whether the customer's operational problem is specific enough to compare.
Implementation depth15/25
Rewards named components, data flow, integrations, and architecture detail.
Outcome specificity20/20
Measures whether the reported benefit is concrete rather than a generic claim.
Quantified impact25/25
2 metrics describe measurable impact.
Deployment scale5/10
Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence90%
Source authority20/25
The main evidence is an official vendor-published customer story.
Claim traceability23/25
11 of 12 key fields link to a named source.
Direct evidence20/20
6 direct source quotes retained.
Date provenance8/10
The publication date comes from publisher-controlled metadata.
The page's Organization JSON-LD lists numberOfEmployees value 117, and the visible page text says Read AI has approximately 117 employees as of August 2026.
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