ActiveFence CEO Noam Schwartz discusses how his company evolved from protecting platforms against user-generated harmful content to helping companies deploy public-facing AI safely at scale.

Topics Include:

• Noam Schwartz introduces himself as ActiveFence CEO
• Former intelligence officer specializing in open source intelligence
• Mission: protect online experiences for everyone everywhere
• Online platforms constantly hammered by various attacks
• Attacks include cybersecurity, abuse, hate speech, spam
• Companies playing endless whack-a-mole game with violations
• Need scalable solution that works across languages/formats
• Developed enterprise-grade technology for sophisticated companies
• Amazon became customer and great partner early on
• Generative AI introduction changed the game completely
• LLMs non-deterministic unlike traditional programmed chatbots
• Same input produces different outputs each time
• AI deployed in customer support, healthcare, airlines
• New risks when models speak on company's behalf
• One bad output creates legal and reputational damage
• Companies need to deploy public-facing AI safely
• Transition affects healthcare, finance, gaming, government sectors
• Building on years of user-generated content expertise
• No specific ChatGPT moment triggered their AI pivot
• ActiveFence was AI company since day one
• Model companies like Amazon, Nvidia asked for help
• Realized their expertise perfectly suited for AI safety
• Staying on top of AI developments is impossible
• Focus on customer adoption, not every new release
• Main enterprise challenge is trusting AI technology
• Unrealistic expectations for 100% accuracy from AI
• Most companies will license existing models, not build
• Security solutions remain independent like traditional cybersecurity

Participants:

• Noam Schwartz – CEO and Co-Founder, ActiveFence
• Ofer Oringher – Software and Technology Account Manager, AWS

See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Jeff Moncrief discusses Sonrai Security's Cloud Permissions Firewall, and the best practices for using AI-powered summaries and orchestration to ensure security at all points.

Topics Include:

• Jeff Moncrief introduces Sonrai Security and Cloud Permissions Firewall
• Focus on achieving least privilege access in AWS quickly
• Lightweight orchestration layer secures IAM from inside out
• Eliminates need to write hundreds of individual policies
• Customers struggle with identity risk in CNAP/CSPM tools
• Generative AI adoption driving top security use cases
• Bedrock and AI agents mentioned daily by customers
• Product managers should consider underlying platform security risks
• AI models have control over infrastructure they run on
• Identity is fundamental infrastructure enabling AWS AI models
• Sonrai uses Bedrock capability inside Cloud Permissions Firewall
• Just-in-time access provides temporary, time-boxed AWS access
• Bedrock generates session summaries from audit logs automatically
• Plain English insights show what happened during sessions
• Session summaries improve audit compliance and incident response
• Customer with 1000 accounts manually deployed service controls
• Friday afternoon deployment caused very bad weekend disaster
• Policy inheritance issues broke child accounts and OUs
• Planning and orchestration essential for scaling AI security
• Sonrai platform built 100% cloud-native on AWS
• Coordinates service control policies and resource control policies
• Just-in-time access relies on IAM Identity Center
• Participates in ISV Accelerate and AWS Marketplace
• Security best practices start with identity as foundation
• "Hackers don't hack, they just log in" philosophy
• Eliminate standing privileges with just-in-time access patterns
• Restrict AI services by user, location, and account
• Review over-permissioned or inactive third-party vendor access
• Actionable insights through useful logging and AI summarization
• Future focus on protecting new services and permissions

Participants:

• Jeff Moncrief – Field CTO & Director of Sales Engineering, Sonrai Security

Links:

• Website – Sonraisecurity.com
• AWS Marketplace – Sonrai Security

See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Akanksha Bilani of Intel shares how businesses can successfully adopt generative AI with significant performance gains while saving on costs.

Topics Include:

• Akanksha runs go-to-market team for Amazon at Intel
• Personal and business devices transformed how we communicate
• Forrester predicts 500 billion connected devices by 2026
• 5,000 billion sensors will be smartly connected online
• 40% of machines will communicate machine-to-machine
• We're living in a world of data deluge
• AI and Gen AI help make data effective
• Goal is making businesses more profitable and effective
• Various industries need Gen AI and data transformation
• Intel advises companies as partners with AWS
• Three factors determine which Gen AI use cases adopt
• Factor one: availability and ease of use cases
• How unique and important are they for business?
• Does it have enough data for right analytics?
• Factor two: purchasing power for Gen AI adoption
• 70% of companies target Gen AI but lack clarity
• Leaders must ensure capability and purchasing power exist
• Factor three: necessary skill sets for implementation
• Need access to right partnerships if lacking skills
• Intel and AWS partnered for 18 years since inception
• Intel provides latest silicon customized for Amazon services
• Engineer-to-engineer collaboration on each processor generation
• 92% of EC2 runs on Intel processors
• Intel powers compute capability for EC2-based services
• Intel ensures access to skillsets making cloud alive
• AWS services include Bedrock, SageMaker, DLAMIs, Kinesis
• Performance is the top three priorities for success
• Not every use case requires expensive GPU accelerators
• CPUs can power AI inference and training effectively
• Every GPU has a CPU head node component

Participants:

• Akanksha Bilani – Global Sales Director, Intel

See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon/isv/

Victoria Chin of Asana and Michael Horn of AWS demonstrate how Amazon Q integrates with Asana to enable AI-powered workflows while dramatically reducing manual work and improving cross-functional collaboration.

Topics Include:

• Victoria Chin introduces herself as Asana's CPO Chief of Staff
• Michael Horn from AWS discusses customer feedback on generative AI
• AI agents limited by quality of data pulled into them
• Amazon Q Business created to analyze information and take action
• Hundreds of customers using Q Business across various industries daily
• AWS hosts most business applications, ideal for AI journey
• Amazon Q has most built-in, managed, secure data connectors available
• Q Index creates comprehensive, accessible index of all company data
• Security permissions automatically pulled in, no manual configuration needed
• Supports both structured and unstructured data from multiple sources
• Victoria returns to discuss Asana's integration with Q Index
• Billions invested in integrations, but usage still lags behind
• Teams switch between apps 1000 times daily, missing connections
• Root problem: no reliable way to track who/what/when/why
• Content platforms store work but don't manage or coordinate
• Asana bridges content and communication for effective teamwork scaling
• AI disrupting software, but questions remain about real value
• Software must provide structured framework to guide LLMs effectively
• AI needs data AND structure to separate signal from noise
• Asana Work Graph maps how work actually gets done organizationally
• Work Graph visualized as interconnected data, not rows and columns
• Most strategic work is cross-functional, requiring multiple teams collaborating
• Traditional integrations require manual setup and knowing when to use
• Q Index gives Asana access to 40+ different data connectors
• Users can ask questions, get answers with cross-application context
• AI Studio enables no-code building of workflows with AI agents
• Product launch example shows intake, planning, execution, and reporting stages
• AI can surface relevant documents, research, and updates automatically
• Chat is tip of iceberg; real power comes from embedded workflows
• Integration evolves from feature-level to AI-powered product-level connections

Participants:

• Victoria J. Chin – Chief of Staff / Product Strategy, AI, Asana
• Michael Horn – Principal Head of Business Development – Artificial Intelligence & Machine Learning, AWS

See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon/isv/

AWS leaders commemorate the podcast's 100th episode while looking ahead to expanded coverage of technology partners and continued focus on generative AI, modern data strategies, agentic AI solutions and more!

Topics Include:

• Episode 100 celebrates milestone of AWS software companies podcast
• Weekly podcast shares ISV stories, best practices, guidance
• Today features AWS leader thoughts on ISV community
• Arym Diamond heads North America data and AI sales
• Specialist team helps win deals, create happy customers
• ISV customers do cutting-edge work on AWS platform
• ISVs create force multiplier effect for entire company
• Building community through podcast video and audio content
• Kristen Backeberg leads global ISV partner marketing at AWS
• Podcast featured 157 ISV leaders from 121 companies
• Reached over 30,000 listeners across 90+ countries worldwide
• ISV partners drive cloud innovation across all industries
• AWS supports growth from startups to enterprise leaders
• APN network designed to help partners succeed, scale
• Olawale Oladehin directs ISV solutions architecture in North America
• Podcast shares customer insights, journeys, and innovations
• AWS technology continues evolving to meet customer needs
• Carol Potts leads North America ISV sales at AWS
• Podcast started less than two years ago
• First episode titled "Data the Engine for Growth"
• Customer obsession drives everything AWS does for ISVs
• Deep collaboration focused on joint ISV success partnerships
• Vishal Sanghvi heads ISV marketing for North America
• ISVs face pressure delivering products at generative AI pace
• Modern data strategy foundational for ISV product success
• Favorite episodes include Snowflake, Wiz, Coupang discussions
• AWS offers programs for every ISV persona type
• Future episodes focus on generative AI, cybersecurity, data
• Agentic AI becoming important for production phase evolution
• Podcast expanding scope to include technology partners

Participants:

• Kristen Backeberg – Director, Global ISV, Solutions Enterprise and Alliance Partner Marketing, Amazon Web Services
• Arym Diamond – Director, US ISV Specialists, Amazon Web Services
• Olawale Oladehin – Director, ISV, Solutions Architecture, North America, Amazon Web Services
• Carol Potts – GM, ISV Sales Segment, North America, Amazon Web Services
• Vishal Sanghvi - Head of ISV Field Marketing, North America, Amazon Web Services

See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Executive leaders from UneeQ and Zeta Global discuss the revolutionary impact of AI technologies that enable enhanced customer experiences and improved sales performances.

Topics Include:

• Dave Cristini introduces panel on AI in advertising and marketing.
• Panel explores personalized experiences at scale with privacy focus.
• UneeQ creates AI-powered digital humans for brand interactions.
• Zeta Global uses AI to optimize customer messaging.
• LLMs combined with traditional ML empowers marketers to create models.
• Marketers can now build models without needing data scientists.
• AI agents integrated into systems can take action, not just respond.
• Agent chaining orchestrates sophisticated marketing actions automatically.
• AWS Bedrock provides tools to shape AI marketing future.
• Hyper-personalization becoming more achievable through AI automation.
• Ethics requires authenticity in brand AI representation.
• Transparency about data usage builds customer trust.
• Win-win approach: AI should augment teams, not just reduce costs.
• Integration difficulties remain a major challenge for AI implementation.
• AI agents have limited context windows and memory.
• Solution: Create specialized agents with persistent viewpoints.
• Companies need strong integration capabilities before implementing AI.
• Privacy regulations impact AI use in global marketing.
• Highly regulated industries require careful AI implementation strategies.
• Generative AI creates compliance challenges with unpredictable outputs.
• Digital humans eliminate judgment, revealing new customer insights.
• Banking clients discovered customers didn't understand financial terminology.
• Zeta improved onboarding with AI agents for data mapping.
• AI data mapping increased NPS scores and accelerated monetization.
• CMOs and CIOs increasingly collaborating on AI initiatives.
• Tension exists between marketing (quick wins) and IT (security).
• Strategic alignment with approved infrastructure enables scaling AI solutions.
• CEOs have critical role in aligning AI goals across departments.
• Internal AI use case: practicing sales with digital humans.
• Sales teams achieved 500% higher sales through AI role-playing.

Participants:

• Danny Tomsett – Chief Executive Officer, UneeQ
• Roman Gun – Vice President, Product, Zeta Global
• David Cristini – Director, ISV Sales, North America – Business Applications, AWS

See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Ash Pembroke, Portfolio CTO of Caylent, discusses the critical balance of data accuracy in the era of Gen AI for the benefit of boosting innovation.

Topics Include:

• Ash Pembroke, Portfolio CTO of Caylent, self-identifies as a "recovering data scientist."
• Caylent is an AWS native services company.
• Data quality remains an issue despite Gen AI.
• Contrasts legalism versus mysticism in data quality.
• Legalism: accurate data when applications need it.
• Mysticism: insights that help decision-making.
• Traditional data foundations approach is being challenged weekly.
• Gen AI developments force rethinking of solution architectures.
• Teams share solutions through giant Slack threads.
• Example: Vector databases questioned after model context protocol.
• Still do traditional data assessments, but stay flexible.
• Integration and data processing constantly get abstracted.
• Data strategy equals architecture strategy equals business strategy.
• Traditional approach: standardize data across engineering teams.
• New approach: allow business users to innovate.
• Bring valuable techniques back to the organization.
• Case study: North Sea wind turbine alerts.
• Initially seen as data quality issue, revealed new predictive failure signal.
• Gen AI enables local experimentation by business users.
• Blurring lines between enterprise enablement and software building.
• BrainBox AI case study: energy optimization across buildings.
• Architecture decisions impact ability to scale products.
• Work with business edges rather than looking for patterns.
• Gen AI can process information from these working groups.
• Think about data as a product, not asset.
• Redimensionalize dependencies across your organization.
• Now's a good time to attack data quality.
• New tools help visualize complexity across organizations.

Participants:

· Ash Pembroke – Portfolio CTO, Caylent

See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

New Relic's Head of AI and ML Innovation, Camden Swita discusses their four-cornered AI strategy and envisions a future of "agentic orchestration" with specialized agents.

Topics Include:

• Introduction of Camden Swita, Head of AI at New Relic.
• New Relic invented the observability space for monitoring applications.
• Started with Java workloads monitoring and APM.
• Evolved into full-stack observability with infrastructure and browser monitoring.
• Uses advanced query language (NRQL) with time series database.
• AI strategy focuses on AI ops for automation.
• First cornerstone: Intelligent detection capabilities with machine learning.
• Second cornerstone: Incident response with generative AI assistance.
• Third cornerstone: Problem management with root cause analysis.
• Fourth cornerstone: Knowledge management to improve future detection.
• Initially overwhelmed by "ocean of possibilities" with LLMs.
• Needed narrow scope and guardrails for measurable progress.
• Natural language to NRQL translation proved immensely complex.
• Selecting from thousands of possible events caused accuracy issues.
• Shifted from "one tool" approach to many specialized tools.
• Created routing layer to select right tool for each job.
• Evaluation of NRQL is challenging even when syntactically correct.
• Implemented multi-stage validation with user confirmation step.
• AWS partnership involves fine-tuning models for NRQL translation.
• Using Bedrock to select appropriate models for different tasks.
• Initially advised prototyping on biggest, best available models.
• Now recommends considering specialized, targeted models from start.
• Agent development platforms have improved significantly since beginning.
• Future focus: "Agentic orchestration" with specialized agents.
• Envisions agents communicating through APIs without human prompts.
• Integration with AWS tools like Amazon Q.
• Industry possibly plateauing in large language model improvements.
• Increasing focus on inference-time compute in newer models.
• Context and quality prompts remain crucial despite model advances.
• Potential pros and cons to inference-time compute approach.

Participants:

• Camden Swita – Head of AI & ML Innovation, Product Management, New Relic

See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/