Gen Digital launches Norton Revamp with real-time AI news engine

A new era for online reputation

In a digital landscape where recruiters and clients prioritize online presence, Gen Digital launched Norton Revamp to help professionals manage their reputations. The platform aims to help ambitious individuals establish themselves as thought leaders by reacting to current breakthroughs rather than old headlines. It addresses the challenge of navigating a feed flooded with AI-generated noise by prioritizing authenticity and timeliness.

The core of the platform is an AI-curated News Engine designed to surface the latest articles and trending topics tied to a user's specific goals. For example, a cybersecurity expert would see a feed prioritized with today's threat intelligence, while a marketing leader would see recent industry shifts. This ensures that the content users interact with is always relevant to their specific professional domain.

Unlike traditional RSS aggregators, this system acts as a goal-aware discovery engine that refreshes with every session. It doesn't just provide a list of links; it actively helps users turn these real-time insights into engaging social media posts. By grounding every suggestion in current, cited web knowledge, the platform helps users maintain a consistent and timely online voice.

How the News Engine works

The platform utilizes Web Search on Amazon Bedrock AgentCore, which is a fully managed web search capability compliant with the Model Context Protocol (MCP). When a user sets a goal, the system uses Amazon Nova to generate targeted search queries based on recent activity and engagement patterns. The agent then sends these queries to AgentCore Web Search to retrieve relevant snippets, source URLs, titles, and publication dates.

Once the search results are returned, an AI Learning System ranks them based on relevance, recency, and source credibility. These ranked results serve as grounding context for Amazon Nova Lite, which then generates content suggestions in the user's authentic voice. This architecture ensures that the AI does not rely on a static knowledge base, which would eventually become stale or outdated.

To manage the flow of information, the team implemented a three-step coaching process consisting of Analyze, Refine, and Post. This flow walks users from initial ideas to published content on platforms like LinkedIn and X. The system also incorporates a feedback loop, allowing the AI to become sharper and more personalized with every iteration of content created by the user.

Technical architecture and stack

The integration follows an event-driven architecture designed to handle personalized news feeds at scale. The backend is built using Node.js, Amazon Elastic Container Service (Amazon ECS), AWS Lambda, and Amazon DynamoDB. The frontend utilizes React, TypeScript, and Tailwind CSS, while the entire infrastructure is managed through Terraform to support blue-green deployments for zero-downtime releases.

The processing pipeline consists of four distinct stages to maintain the platform's data integrity. A Full Scan pulls up to 1,000 historical posts into Amazon S3 for reputation impact analysis. A Daily Scan performs incremental analysis triggered by Amazon EventBridge, while Weekly Goal Generation uses Lambda to create new milestones based on engagement data and real-time trends.

The generative AI stack is diverse, using Amazon Bedrock as the core engine for content generation and personalization. Amazon Nova (Nova Lite) powers the primary large language model tasks like goal creation and trend analysis. Additionally, the team uses Stability AI for image generation and Claude for complex reasoning tasks, ensuring a robust suite of capabilities for the user.

Accelerated development methods

Gen Digital adopted an AI-native development mindset, using generative AI to handle code generation, documentation, and test scaffolding. By using Claude, the team was able to produce 10 or more design variants per concept and compress design-to-prototype time from weeks to hours. They reported that AI generated 70 percent of the UI code and accelerated boilerplate generation by 90 percent.

While AI handled the heavy lifting of implementation, humans remained responsible for high-level architecture decisions, security reviews, and business logic. The team found that while AI accelerated the process, human judgment was still required for experience-based tasks like designing the DynamoDB multi-table architecture. This separation of concerns allowed the team to achieve 3x faster feature implementation compared to traditional methods.

The development process also included rigorous testing and security protocols to protect the Norton brand. The team achieved 85 percent code coverage through automated test generation, focusing on content quality and news feed relevance. Security checks spanned static code analysis and generative AI model output validation, resulting in 99.9 percent uptime since the platform's launch in March 2026.

Best practices for real-time grounding

For organizations looking to implement similar real-time grounding, the Gen Digital team suggests focusing on well-structured query generation. They found that precise prompt engineering for queries yields significantly better results than open-ended questions. To balance freshness with efficiency, they also recommend caching results with time-to-live (TTL) values that match specific freshness requirements.

Another key strategy is building feedback loops to track which web search results users actually engage with. The Norton Revamp News Engine saw a measurable improvement in relevance over its first 90 days by feeding these engagement signals back into the query generation process. This allows the system to learn what information is most valuable to the user over time.

Finally, validating source quality is essential for maintaining trust and authority. Because AgentCore Web Search returns source URLs and publication dates, the team built a lightweight credibility scoring layer. This layer prioritizes authoritative sources, ensuring that the AI-curated news feed remains a reliable tool for professional reputation management.