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:
- 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.
- 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.
- 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.
- 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.
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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.
