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AWS Software / SaaS Global

Goodnotes

Enterprise Knowledge Search

Founded in 2011, Goodnotes has been a leader in digital note-taking and productivity, now serving over 24 million monthly active users. As a pioneer in digital handwriting, Goodnotes was among the first apps to support the Apple Pencil when it launched in 2015.

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Founded in 2011, Goodnotes has been a leader in digital note-taking and productivity, now serving over 24 million monthly active users.
This infrastructure, combined with Amazon Elastic Compute Cloud (Amazon EC2) instances and Elastic Load Balancing , reduced latency and cut costs by 97 percent compared to...

Reported impact

Business outcome

By utilizing the performance, scalability, and cost-effectiveness of running its LLM on AWS, Goodnotes has been able to speed up the development of new generative AI features for its app.

  • Customer Experience
  • Scalability
  • Speed to Market

Solution

Goodnotes , known for its digital note-taking and productivity app, aimed to enhance its generative AI capabilities by refining its AI infrastructure to improve scalability and cost-effectiveness. This ensures the platform can handle growing user demand while maintaining high performance and keeping operational costs low. In 2024, Goodnotes transitioned from a self-hosted model on Amazon Elastic Kubernetes Service (Amazon EKS) to Anthropic Claude on Amazon Bedrock to support the launch of its AI-powered Ask Goodnotes feature. This feature empowers users to leverage generative AI to explore, learn from, and build on the knowledge and ideas captured in their Goodnotes notebooks. This fully managed service helped Goodnotes accelerate its go-to-market efforts and minimize the time and resources required for infrastructure management, allowing the team to focus on advancing AI development, while ensuring rapid scalability to meet increasing user demand.

Data flow

To deliver its generative AI capabilities at scale and streamline its development process, Goodnotes transitioned to using Amazon Bedrock to access selected LLMs. "With Amazon Bedrock, we have streamlined AI feature delivery, accelerated innovation and iteration, and focused more on optimizing the user experience," explains Angus Fong, AI team lead and engineering manager at Goodnotes. AWS supported this launch by monitoring performance and offering development frameworks that accelerated deployment.

Solution architecture

5 components · 2 layers
  1. Compute
    • Amazon Bedrock Runs the foundation model layer for the knowledge search and question-answering workflows.
    • Anthropic Claude Provides a large language model used by the knowledge search and question-answering workflows.
    • Amazon EKS Runs containerized services that deliver the knowledge search and question-answering workflows.
  2. Governance
    • Amazon CloudWatch Monitors usage and operations for the knowledge search and question-answering workflows.
    • Amazon GuardDuty Monitors threats and security signals around the knowledge search and question-answering workflows.

Architecture clues

  • Additionally, with AWS' support, Goodnotes transitioned to a cross-region inference architecture, minimizing risks tied to single host locations and improving service availability.
  • Even after opening access to millions of users, Goodnotes was able to achieve high reliability for its main API service supporting Ask Goodnotes.
  • In 2024, Goodnotes transitioned from a self-hosted model on Amazon Elastic Kubernetes Service (Amazon EKS) to Anthropic Claude on Amazon Bedrock to support the launch of its AI-powered Ask Goodnotes...
  • Steven Chan, founder and CEO at Goodnotes, adds, "Working with AWS enables us to provide Goodnotes users with the best LLM-powered experience by allowing rapid testing of various models during...

Evidence from the source

Founded in 2011, Goodnotes has been a leader in digital note-taking and productivity, now serving over 24 million monthly active users.
Goodnotes , known for its digital note-taking and productivity app, aimed to enhance its generative AI capabilities by refining its AI infrastructure to improve scalability and cost-effectiveness.
Goodnotes has invested significantly in AI and ML to improve user efficiency and enhance the experience of work and study.
In 2024, Goodnotes transitioned from a self-hosted model on Amazon Elastic Kubernetes Service (Amazon EKS) to Anthropic Claude on Amazon Bedrock to support the launch of its AI-powered Ask Goodnotes feature.
This infrastructure, combined with Amazon Elastic Compute Cloud (Amazon EC2) instances and Elastic Load Balancing , reduced latency and cut costs by 97 percent compared to SaaS-based LLMs.
To support some of these new features, initially, Goodnotes adopted a large language model (LLM) on Amazon Elastic Kubernetes Services (Amazon EKS), leveraging a GPU-based cluster for scalable, cost-effective performance.
Transparency Evidence & methodology 95/100 reference value · 90% confidence · 2 sources

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 value95/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth20/25
    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 scale10/10
    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.
  • Source transparency9/10
    2 source references document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity10/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. AWS

    Goodnotes customer story

    First-party
    https://aws.amazon.com/solutions/case-studies/goodnotes/
    Source type
    Vendor-published customer story
    Published
    Dec 11, 2024
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes
    • Publication date
  2. Goodnotes

    How We Work: Our Seven Company Values

    First-party
    https://www.goodnotes.com/blog/seven-goodnotes-company-values

    Today, over 300 people work at Goodnotes, and our colleagues span across the globe.

    Source type
    Official company website
    Supports
    • Company size

Date evidence

Not separately sourced Industry, Region. Treat these normalized attributes as lower-confidence until a dedicated source is added.

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