The funding and overall future of Head Start — which helps low-income families with child development and family support services — has been in the headlines for the better half of the year because of potential program cuts, followed by lawsuits, then think pieces and statements lauding its benefits.

The program, which is turning 60 this year and has served more than 40 million families, appears to be in the calm amid the eye of the storm. Local Head Start offices are largely operating business as usual, but leaders have bated breath — the future of its funding will be decided on Oct. 1.

While it may come into an additional $85 million windfall, or maintain its $12.2 billion in funding, both local and national Head Start officials have concerns that either scenario will not be enough.

“On the one hand we’re relieved that the initial proposal to eliminate Head Start is out of the way and we don’t have to have those conversations,” says Michelle Haimowitz, executive director of the Massachusetts Head Start Association. “But another year of flat funding would continue to cut us off at the knees. And the costs don’t magically stay flat; the only way to do that is cut enrollment and make other changes we don’t want to make.”

The concern comes amid months of confusion for staff and parents on the fate of Head Start. In April, leaked documents detailing fiscal year 2026 budgets revealed plans to cut Head Start funding entirely. That same month, four state Head Start advocacy organizations — Illinois, Pennsylvania, Washington and Wisconsin — and two parent groups sued the Trump administration over potential spending cuts on diversity, equity and inclusion initiatives.

The yo-yoing policy proposals brought delays in accessing funds. Megan Woller, executive director of Idaho’s Head Start Association, recalls one local Head Start office considered taking out a loan in July in order to pay staff before the funding came through. Haimowitz added the Massachusetts offices saw “significant” delays in the first half of the year accessing funds and getting grant approvals. Many Head Start offices across the nation, including in Washington, Mississippi and Illinois, have reported experiencing confusion, but meanwhile others, including in Colorado, Ohio and Virginia, are expanding.

The administrative funding hiccups were exacerbated by the stress of not being able to reach regional federal Head Start offices: In April, the 10 Head Start offices that helped local Head Start offices throughout the country were whittled down to five, with the remaining half of offices in Boston, Chicago, New York, San Francisco and Seattle closing. The closures followed plans to reduce the scope of the U.S. Department of Health and Human Services.

“While program specialists are doing everything they can to support us, their capacity to be as communicative and in touch as our program specialist in the Boston office — when they had half as many cases — is going to be significantly diminished,” Haimowitz says.

It also created confusion among parents who did not know the shuttered regional offices did not directly serve children, and instead were intermediaries.

“People got confused because they don’t know who that is; that it’s the federal government supporting the grantees, it’s not your kids’ center,” Woller says. “But the public doesn’t know the difference between all this. I was getting calls of ‘Wait, is my kid’s center closed tomorrow?’”

The funding hangups have largely been alleviated for now — Woller and Haimowitz both said the delays are continuing but seem to be improving — but a collective breath is being held as the future of Head Start’s funding remains in flux. While the Senate Appropriations Committee recommended an $85 million increase to Head Start funding in July — a roughly 0.6 percent bump — on Sept. 2, the House Appropriations Committee pushed the bill forward, proposing maintaining its current level of funding of $12.2 billion. The full Senate and House still need to give final approval and have until Oct. 1 to do so.

‘There Is No Plan B’

Tommy Sheridan, deputy director of the National Head Start Association, has served in the role for close to two decades. He acknowledged Head Start has been a pawn in political games on both sides of the aisle long before this year, pointing to a proposed funding cut in 2011 that was ultimately reversed, and the sequestration efforts in 2013.

Critics of Head Start have argued that it doesn’t produce strong enough outcomes for families to justify taxpayer support. Supporters contest that characterization.

Sheridan maintains what he calls a “cautious optimism” when it comes to the program’s funding future.

“Yes, we’ve seen those types of stressors and feel very confident Congress and the president will continue to keep their commitment to support families in every corner of the country,” he says. “Sometimes you have to take a step back to go forward; it feels that’s where the conversation has been, but we’re excited to move forward.”

However, what is unique in this year’s case is the possibility for Head Start’s funding to stay flat. The federal program has only had three instances over six decades when it did not receive an increase in funding, according to Sheridan. If the government decides to keep its funding flat yet again for the program this year, it would be the first time in its history that it did not receive a funding boost two fiscal years in a row.

Even if the 0.6 percent proposed increase for Head Start funding were enacted, it would not keep up with the rising cost of living — Social Security benefits, for example, increased 2.5 percent to account for cost of living in 2025. Each state has its own amount of Head Start funding, with some receiving more than others due to additional state investments. Massachusetts, for example, allocated an additional $20 million for the Head Start Supplemental Grant in fiscal year 2025, largely to boost classroom teacher salaries.

“Our concern is the fact we’re facing incredibly high costs: inflationary costs, rising health care costs, the need to pay staff competitive wages,” Sheridan says. “It’s not like any warm body can work as a Head Start teacher; that is a very specific set of skills, it requires degrees and training. So when we work with our staff and train them up, we want to reward them. With seeing flat funding, programs do have to make those cuts somewhere.”

The early childhood education sector is already battling with keeping its workforce, which has long been plagued by low wages. Woller says concern over the future of funding could accelerate the workforce exodus.

“The purpose of Head Start is to help lift families out of poverty, but we have to demonstrate that in part in how we pay the staff, and it’s really hard when the funding is as low as it is,” she says. “And when staff see everything crumbling at the federal level, they may look elsewhere; that’s also a big concern.”

There are also no viable alternative funding pathways, according to local and national officials. Head Start services are free for families.

“The types of services that Head Start provides take manpower other streams of child care funding don’t support,” Haimowitz says. “The state supplement has been growing and we’re incredibly grateful for that, but no alternative source is going to meet the types of needs that Head Start funding provides.”

Woller put it more simply.

“No, there is no Plan B,” she says with a self-defeated laugh. “There’s no backup plan when it’s this amount of dollars.”

Serving All Children?

There’s the added confusion of the recently announced policy change to reclassify Head Start as a federal public benefit, which would bar non-U.S. citizens from enrolling in Head Start services. There are currently no systems in place to check for immigration status.

The policy idea has not been passed as of the beginning of September. Both regional and national Head Start officials say they have not been given any directive or guidance to enforce these proposed rules, and that all families that were eligible for Head Start according to preexisting guidelines continue to be.

“Philosophically, the Head Start promise is all children, regardless of circumstance at birth, can succeed at school and life,” Woller says. “We want to make sure we uphold that.”

While the funding future of Head Start remains in flux, officials are trying to spread the word that the programming remains open and available for any one that needs it.

“The tough part is the uncertainty and lack of answers; that’s the part that’s keeping folks up at night,” Haimowitz says. “There are so few answers for all the questions we have, and directors are trying to keep their teachers on staff, keep families feeling comfortable and showing Head Start is open and enrolling amidst all this real uncertainty. It’s tough.”

Since its general availability in 2024, Amazon Q Business (Amazon Q) has enabled independent software vendors (ISVs) to enhance their Software as a Service (SaaS) solutions through secure access to customers’ enterprise data by becoming Amazon Q Business data accessor. To find out more on data accessor, see this page. The data accessor now supports trusted identity propagation. With trusted token issuer (TTI) authorization support, ISVs as data accessor can integrate with Amazon Q index while maintaining enterprise-grade security standards for their software-as-a-service (SaaS) solutions.

Prior to TTI support, data accessors needed to implement authorization code flow with AWS IAM Identity Center integration when accessing the Amazon Q index. With TTI support for data accessors, ISVs can now use their own OpenID Provider to authenticate enterprise users, alleviating the need for double authentication while maintaining security standards.

In this blog post, we show you how to implement TTI authorization for data accessors, compare authentication options, and provide step-by-step guidance for both ISVs and enterprises.

Prerequisites

Before you begin, make sure you have the following requirements:

• An AWS account with administrator access
• Access to Amazon Q Business
• For ISVs:
  • An OpenID Connect (OIDC) compatible authorization server
• For enterprises:
  • Amazon Q Business administrator access
  • Permission to create trusted token issuers

Solution Overview

This solution demonstrates how to implement TTI authentication for Amazon Q Business data accessors. The following diagram illustrates the overall flow between different resources, from ISV becoming a data accessor, customer enabling ISV data accessor, to ISV accessing customer’s Amazon Q index:

Understanding Trusted Token Issuer Authentication

Trusted Token Issuer represents an advanced identity integration capability for Amazon Q. At its core, TTI is a token exchange API that propagates identity information into IAM role sessions, enabling AWS services to make authorization decisions based on the actual end user’s identity and group memberships. This mechanism allows AWS services to apply authorization and security controls based on the authenticated user context. The TTI support simplifies the identity integration process while maintaining robust security standards, making it possible for organizations to ensure that access to Amazon Q respects user-level permissions and group memberships. This enables fine-grained access control and maintains proper security governance within Amazon Q implementations.

Trusted Token Issuer authentication simplifies the identity integration process for Amazon Q by enabling the propagation of user identity information into AWS IAM role sessions. Each token exchange allows AWS services to make authorization decisions based on the authenticated user’s identity and group memberships. The TTI support streamlines the integration process while maintaining robust security standards, enabling organizations to implement appropriate access controls within their Amazon Q implementations.

Understanding Data Accessors

A data accessor is an ISV that has registered with AWS and is authorized to use their customers’ Amazon Q index for the ISV’s Large Language Model (LLM) solution. The process begins with ISV registration, where they provide configuration information including display name, business logo, and OpenID Connect (OIDC) configuration details for TTI support.

During ISV registration, providers must specify their tenantId configuration – a unique identifier for their application tenant. This identifier might be known by different names in various applications (such as Workspace ID in Slack or Domain ID in Asana) and is required for proper customer isolation in multi-tenant environments.

Amazon Q customers then add the ISV as a data accessor to their environment, granting access to their Amazon Q index based on specific permissions and data source selections. Once authorized, the ISV can query the customers’ index through API requests using their TTI authentication flow, creating a secure and controlled pathway for accessing customer data.

Implementing TTI Authentication for Amazon Q index Access

This section explains how to implement TTI authentication for accessing the Amazon Q index. The implementation involves initial setup by the customer and subsequent authentication flow implemented by data accessors for user access.

TTI provides capabilities that enable identity-enhanced IAM role sessions through Trusted Identity Propagation (TIP), allowing AWS services to make authorization decisions based on authenticated user identities and group memberships. Here’s how it works:

To enable data accessor access to a customer’s Amazon Q index through TTI, customers must perform an initial one-time setup by adding a data accessor on Amazon Q Business application. During setup, a TTI with the data accessor’s identity provider information is created in the customer’s AWS IAM Identity Center, allowing the data accessor’s identity provider to authenticate access to the customer’s Amazon Q index.

The process to set up an ISV data accessor with TTI authentication consists of the following steps:

1. The customer’s IT administrator accesses their Amazon Q Business application and creates a trusted token issuer with the ISV’s OAuth information. This returns a TrustedTokenIssuer (TTI) Amazon Resource Name (ARN).
   
2. The IT administrator creates an ISV data accessor with the TTI ARN received in Step 1.
3. Amazon Q Business confirms the provided TTI ARN with AWS IAM Identity Center and creates a data accessor application.
4. Upon successful creation of the ISV data accessor, the IT administrator receives data accessor details to share with the ISV.
5. The IT administrator provides these details to the ISV application.

Once the data accessor setup is complete in the customer’s Amazon Q environment, users can access the Amazon Q index through the ISV application by authenticating only against the data accessor’s identity provider.

The authentication flow proceeds as follows:

1. A user authenticates against the data accessor’s identity provider through the ISV application. The ISV application receives an ID token for that user, generated from the ISV’s identity provider with the same client ID registered on their data accessor.
2. The ISV application needs to use the AWS Identity and Access Management (IAM) role that they created during the data accessor onboarding process by calling AssumeRole API, then make CreateTokenWithIAM API request to the customer’s AWS IAM Identity Center with the ID token. AWS IAM Identity Center validates the ID token with the ISV’s identity provider and returns an IAM Identity Center token.
3. The ISV application requests an AssumeRole API with: IAM Identity Center token, extracted identity context, and tenantId. The tenantId is a security control jointly established between the ISV and their customer, with the customer maintaining control over how it’s used in their trust relationships. This combination facilitates secure access to the correct customer environment.
4. The ISV application calls the SearchRelevantContent API with the session credentials and receives relevant content from the customer’s Amazon Q index.

When implementing Amazon Q integration, ISVs need to consider two approaches, each with its own benefits and considerations:

TTI excels in providing a seamless user experience through single authentication on the ISV system and enables backend-only implementations for SearchRelevantContent API access without requiring direct user interaction. However, this approach requires ISVs to maintain their own OIDC authorization server, which may present implementation challenges for some organizations. Additionally, some enterprises might have concerns about ISVs having persistent ability to make API requests on behalf of their users without explicit per-session authorization.

Next Steps

For ISVs: Becoming a Data Accessor with TTI Authentication

Getting started on Amazon Q data accessor registration process with TTI authentication is straightforward. If you already have an OIDC compatible authorization server for your application’s authentication, you’re most of the way there.

To begin the registration process, you’ll need to provide the following information:

• Display name and business logo that will be displayed on AWS Management Console
• OIDC configuration details (OIDC ClientId and discovery endpoint URL)
• TenantID configuration details that specify how your application identifies different customer environments

For details, see Information to be provided to the Amazon Q Business team.

For ISVs using Amazon Cognito as their OIDC authorization server, here’s how to retrieve the required OIDC configuration details:

1. To get the OIDC ClientId:- Navigate to the Amazon Cognito console- Select your User Pool- Go to “Applications” > “App clients”- The ClientId is listed under “Client ID” for your app client
2. To get the discovery endpoint URL:- The URL follows this format:https://cognito-idp.{region}.amazonaws.com/{userPoolId}/.well-known/openid-configuration– Replace {region} with your AWS region (e.g., us-east-1)- Replace {userPoolId} with your Cognito User Pool IDFor example, if your User Pool is in us-east-1 with ID ‘us-east-1_abcd1234’, your discovery endpoint URL would be:

   https://cognito-idp.us-east-1.amazonaws.com/us-east-1_abcd1234/.well-known/openid-configuration

Note: While this example uses Amazon Cognito, the process will vary depending on your OIDC provider. Common providers like Auth0, Okta, or custom implementations will have their own methods for accessing these configuration details.

Once registered, you can enhance your generative AI application with the powerful capabilities of Amazon Q, allowing your customers to access their enterprise knowledge base through your familiar interface. AWS provides comprehensive documentation and support to help you implement the authentication flow and API integration efficiently.

For Enterprises: Enabling TTI-authenticated Data Accessor

To enable a TTI-authenticated data accessor, your IT administrator needs to complete the following steps in the Amazon Q console:

1. Create a trusted token issuer using the ISV’s OAuth information
2. Set up the data accessor with the generated TTI ARN
3. Configure appropriate data source access permissions

This streamlined setup allows your users to access Amazon Q index through the ISV’s application using their existing ISV application credentials, alleviating the need for multiple logins while maintaining security controls over your enterprise data.

Both ISVs and enterprises benefit from AWS’s comprehensive documentation and support throughout the implementation process, facilitating a smooth and secure integration experience.

Clean up resources

To avoid unused resources, follow these steps if you no longer need the data accessor:

• Delete the data accessor:
  • On the Amazon Q Business console, choose Data accessors in the navigation pane
  • Select your data accessor and choose Delete.
• Delete the TTI:
  • On the IAM Identity Center console, choose Trusted Token Issuers in the navigation pane.
  • Select the associated issuer and choose Delete.

Conclusion

The introduction of Trusted Token Issuer (TTI) authentication for Amazon Q data accessors marks a significant advancement in how ISVs integrate with Amazon Q Business. By enabling data accessors to use their existing OIDC infrastructure, we’ve alleviated the need for double authentication while maintaining enterprise-grade security standards through TTI’s robust tenant isolation mechanisms and secure multi-tenant access controls, making sure each customer’s data remains protected within their dedicated environment. This streamlined approach not only enhances the end-user experience but also simplifies the integration process for ISVs building generative AI solutions.

In this post, we showed how to implement TTI authentication for Amazon Q data accessors. We covered the setup process for both ISVs and enterprises and demonstrated how TTI authentication simplifies the user experience while maintaining security standards.

To learn more about Amazon Q Business and data accessor integration, refer to Share your enterprise data with data accessors using Amazon Q index and Information to be provided to the Amazon Q Business team. You can also contact your AWS account team for personalized guidance. Visit the Amazon Q Business console to begin using these enhanced authentication capabilities today.

About the Authors

Takeshi Kobayashi is a Senior AI/ML Solutions Architect within the Amazon Q Business team, responsible for developing advanced AI/ML solutions for enterprise customers. With over 14 years of experience at Amazon in AWS, AI/ML, and technology, Takeshi is dedicated to leveraging generative AI and AWS services to build innovative solutions that address customer needs. Based in Seattle, WA, Takeshi is passionate about pushing the boundaries of artificial intelligence and machine learning technologies.

Siddhant Gupta is a Software Development Manager on the Amazon Q team based in Seattle, WA. He is driving innovation and development in cutting-edge AI-powered solutions.

Akhilesh Amara is a Software Development Engineer on the Amazon Q team based in Seattle, WA. He is contributing to the development and enhancement of intelligent and innovative AI tools.

This post was written with Stephen Coverdale and Alessandra Filice of Proofpoint.

At the forefront of cybersecurity innovation, Proofpoint has redefined its professional services by integrating Amazon Q Business, a fully managed, generative AI powered assistant that you can configure to answer questions, provide summaries, generate content, and complete tasks based on your enterprise data. This synergy has transformed how Proofpoint delivers value to its customers, optimizing service efficiency and driving useful insights. In this post, we explore how Amazon Q Business transformed Proofpoint’s professional services, detailing its deployment, functionality, and future roadmap.

We started this journey in January 2024 and launched production use within the services team in October 2024. Since that time, the active users have achieved a 40% productivity increase in administrative tasks, with Amazon Q Apps now saving us over 18,300 hours annually. The impact has been significant given that consultants typically spend about 12 hours per week on non-call administrative tasks.

The time savings are evident in several key areas:

• Over 10,000 hours annually through apps that support customer data analysis and deliver insights and recommendations
• 3,000 hours per year saved in executive reporting generation, which will likely double when we deploy automated presentation creation with AI-powered hyper-personalization
• 1,000 hours annually on meeting summarizations
• 300 hours per year preparing renewal justifications—but the real benefit here is how quickly we can now turn around customized content at a scale we couldn’t achieve before

Beyond these time savings, we’ve seen benefits in upskilling our teams with better access to knowledge, delivering additional value to clients, improving our renewal processes, and gaining deeper customer understanding through Amazon Q Business. This productivity increase means our consultants can focus more time on strategic initiatives and direct customer engagement, ultimately delivering higher value to our customers.

A paradigm shift in cybersecurity service delivery

Proofpoint’s commitment to evolving our customer interactions into delightful experiences led us to adopt Amazon Q Business across our services and consulting teams. This integration has enabled:

• Enhanced productivity – Consultants save significant time on repetitive tasks, reallocating focus to high-value client interactions
• Deeper insights – AI-driven analytics provide a granular understanding of customer environments
• Scalable solutions – Tailored applications (Amazon Q Apps) empower consultants to address customer needs effectively

Transformative use cases through Amazon Q Apps

Amazon Q Business has been instrumental in our deployment, and we’ve developed over 30 custom Amazon Q Apps, each addressing specific challenges within our service portfolio.

Some of the use cases are:

1. Follow-up email automation

• Challenge – Consultants spent hours drafting follow-up emails post-meetings
• Solution – Amazon Q Apps generates curated follow-up emails outlining discussion points and action items
• Impact – Consistent customer tracking, reduced response time, and multilingual capabilities for global reach

2. Health check analysis

• Challenge – Analyzing complex customer health assessments and understanding customer changes over time
• Solution – Amazon Q Apps compares files, providing an overview of key changes between two health checks, and a generated summary to help support customer business reviews (CBRs) and progress updates
• Impact – Improved communication and enhanced customer satisfaction

3. Renewal justifications

• Challenge – Time-intensive preparation for renewal discussions
• Solution – Tailored renewal justification points crafted to demonstrate the value we’re delivering
• Impact – Scalable, targeted value articulation, fostering customer retention

4. Drafting custom responses

• Challenge – Providing in-depth and specific responses for customer inquiries
• Solution – Amazon Q Apps creates a personalized email draft using our best practices and documentation
• Impact – Faster, more accurate communication

The following diagram shows the Proofpoint use cases for Amazon Q Business.

The following diagram shows the Proofpoint implementation. Proofpoint Chat UI is the front end that connects to Amazon Q Business, which connects to data sources in Amazon Simple Storage Service (Amazon S3), Amazon Redshift, Microsoft SharePoint, and Totango.

Data strategy: Laying the foundation to a successful deployment

Proofpoint’s successful integration of Amazon Q Business followed a comprehensive data strategy and a phased deployment approach. The journey involved crucial data preparation and documentation overhaul with key aspects noted below.

Quality documentation:

• Conducted thorough review of existing documentation
• Organized and added metadata to our documentation for improved accessibility
• Established vetting process for new documents

Knowledge capture:

• Developed processes to document tribal knowledge
• Created strategies for ongoing knowledge enrichment
• Established metadata tagging standards for improved searchability

We’ve primarily used Microsoft SharePoint document libraries to manage and support this process, and we’re now replicating this model as we onboard additional teams. Conducting sufficient testing that Amazon Q Business remains accurate is a key to maintaining the high efficacy we’ve seen from the results.

Going forward, we’re also expanding our data strategy to capture more information and insights into our customer journey. We want to make more data sources available to Amazon Q Business to expand this project scope so it covers more work tasks and more teams.

Journey of our successful Amazon Q Business rollout

Through our AWS Enterprise Support relationship, Proofpoint received full support on this project from the AWS account team, who helped us evaluate in detail the viability of the project and use expert technical resources. They engaged fully to help our teams with the use of service features and functionality and gain early usage of new feature previews. These helped us optimize and align our development timelines with the service roadmaps.

We established a rigorous vetting process for new documents to maintain data quality and developed strategies to document institutional knowledge. This made sure our AI assistant was trained in the most accurate and up-to-date information. This process enlightened us to the full benefits of Amazon Q Business.

The pilot and discovery phases were critical in shaping our AI strategy. We quickly identified the limitations of solely having the chat functionality and recognized the game-changing potential of Amazon Q Apps. To make sure we were addressing real needs, we conducted in-depth interviews with consultants to determine pain points so we could then invest in developing the Amazon Q Apps that would provide the most benefits and time savings. App development and refinement became a central focus of our efforts. We spent a significant amount of time prompt engineering our apps to provide consistent high-quality results that would provide practical value to our users and encourage them to adopt the apps as part of their processes. We also continued updating the weighting of our documents, using the metadata to enhance the output. This additional work upfront led to a successful deployment.

Lessons learned

Throughout our journey of integrating Amazon Q Business, we’ve gleaned valuable lessons that have shaped our approach to AI implementation within our services and consulting areas. One of the most compelling insights is the importance of a robust data strategy. We’ve learned that AI is only as smart as we make it, and the quality of data fed into the system directly impacts its performance. This realization led us to invest significant time in identifying avenues to make our AI smarter, with a focus on developing a clear data strategy across our services and consulting teams to make sure we realize the full benefits of AI. We also discovered that having AI thought leaders embedded within our services function is key to the success of AI implementation, to bring that necessary understanding of both the technology and our business processes.

Another lesson was that time investment is required to get the most out of Amazon Q Business. The customization and ongoing management are key to delivering optimal results. We found that creating custom apps is the most effective route to adoption. Amazon Q Business features no-code simplicity for creating the apps by business-oriented teams instead of programmers. The prompt engineering required to provide high-quality and consistent results is a time-intensive process. This underscores the need for dedicated resources with expertise in AI, our business, and our processes.

Experimentation on agentic features

Amazon Q Business has taken a significant leap forward in enhancing workplace productivity with the introduction of an intelligent orchestration feature for Amazon Q Business. This feature transforms how users interact with their enterprise data and applications by automatically directing queries to appropriate data sources and plugins. Instead of manually switching between different work applications, users now seamlessly interact with popular business tools such as Jira, Salesforce, ServiceNow, Smartsheet, and PagerDuty through a single conversational interface. The feature uses Retrieval Augmented Generation (RAG) data for enterprise-specific knowledge and works with both built-in and custom plugins, making it a powerful addition to the workplace technology landscape. We’re experimenting on agentic integration with Totango and a few other custom plugins with Orchestrator and are seeing good results.

Looking ahead

Looking ahead, Proofpoint has outlined an ambitious roadmap for expanding our Amazon Q Business deployment across our customer-facing teams. The key priorities of this roadmap include:

1. Expansion of data sources – Proofpoint will be working to incorporate more data sources, helping to unify our information across our teams and allowing for a more comprehensive view of our customers. This will include using the many Amazon Q Business data source connectors, such as Salesforce, Confluence, Amazon S3, and Smartsheet, and will expand the impact of our Amazon Q Apps.
2. Using Amazon Q Business actions – Building on our successful Amazon Q deployment, Proofpoint is set to enhance its tool integration strategy to further streamline operations and reduce administrative burden. We plan to take advantage of Amazon Q Business actions using the plugin capabilities so we can post data into our different customer success tools. With this integration approach, we can take note of more detailed customer insights. For example, we can capture project progress from a meeting transcript and store it in our customer success tool to identify sentiment concerns. We’ll be able to gather richer data about our customer engagements, which translates to providing even greater and more personalized service to our customers.
3. Automated workflows – Future enhancements will include expanded automation and integrations to further streamline our service delivery. By combining our enhanced data sources with automated actions, we can make sure our teams receive the right information and insights at the right time while reducing manual intervention.
4. Data strategy enhancement – We’ll continue to refine our data strategy across Proofpoint Premium Services, establishing best practices for documentation and implementing systems to record undocumented knowledge. This will include developing better ways to understand and document our customer journey through the integration of various tools and data sources.

Security and compliance

As a cybersecurity leader, Proofpoint makes sure that AI processes comply with strict security and privacy standards:

• Secure integration – Amazon Q Apps seamlessly connects to our various data sources, safeguarding sensitive data
• Continuous monitoring – Embedded feedback mechanisms and daily synchronization uphold quality control

Conclusion: Redefining cybersecurity services

Amazon Q Business exemplifies Proofpoint’s innovative approach to cybersecurity. With Amazon Q Business AI capabilities, we’re elevating our customer experience and scaling our service delivery.

As we refine and expand this program, our focus remains unwavering: delivering unmatched value and protection to our clients. Through Amazon Q Business, Proofpoint continues to set the benchmark in cybersecurity services, making sure organizations can navigate an increasingly complex threat landscape with confidence.

Learn more

About the Authors

Stephen Coverdale is a Senior Manager, Professional Services at Proofpoint. In addition to managing a Professional Services team, he leads an AI integration team developing and driving a strategy to leverage the transformative capabilities of AI within Proofpoint’s services teams to enhance Proofpoint’s client engagements.

Alessandra Filice is a Senior AI Integration Specialist at Proofpoint, where she plays a lead role in implementing AI solutions across Proofpoint’s services teams. In this role, she specializes in developing and deploying AI capabilities to enhance service delivery and operational efficiency. Working closely with stakeholders across Proofpoint, she identifies opportunities for AI implementation, designs innovative solutions, and facilitates successful integration of AI technologies.

Ram Krishnan is a Senior Technical Account Manager at AWS. He serves as a key technical resource for independent software vendor (ISV) customers, providing help and guidance across their AWS needs including AI/ML focus — from adoption and migration to design, deployment, and optimizations across AWS services.

Abhishek Maligehalli Shivalingaiah is a Senior Generative AI Solutions Architect at AWS, specializing in Amazon Q Business. With a deep passion for using agentic AI frameworks to solve complex business challenges, he brings nearly a decade of expertise in developing data and AI solutions that deliver tangible value for enterprises. Beyond his professional endeavors, Abhishek is an artist who finds joy in creating portraits of family and friends, expressing his creativity through various artistic mediums.