AWS for Software Companies Podcast

Latest Episodes:

Ep087: The Multi-Agent Advantage: How Sumo Logic Leverages AI for Observability Mar 25, 2025

Show notes

CEO Joe Kim shares how Sumo Logic has implemented generative AI to democratize data analytics, leveraging AWS Bedrock's multi-agent capabilities to dramatically improve accuracy.

Topics Include:

Introduction of Joe Kim, CEO of Sumo Logic.
Question: Overview of Sumo Logic's products and customers?
Sumo Logic specializes in observability and security markets.
Company leverages industry-leading log management and analytics capabilities.
Question: How has generative AI entered this space?
Kim's background is in product, strategy and engineering.
Non-experts struggle to extract value from complex telemetry data.
Generative AI provides easier interface for interacting with data.
Question: How do you measure success of AI initiatives?
Focus on customer problems, not retrofitting AI everywhere.
Launched "Mo, the co-pilot" at AWS re:Invent.
Mo enables natural language queries of complex data.
Mo suggests visualizations and follow-up questions during incidents.
Question: What challenges did you face implementing AI?
Team knew competitors would eventually implement similar capabilities.
Single model approach topped out at 80% accuracy.
Multi-agent approach with AWS Bedrock achieved mid-90% accuracy.
Bedrock offered security benefits and multiple model capabilities.
Question: How was working with the AWS team?
Partnered with Bedrock team and tribe.ai for implementation.
Partners helped avoid pitfalls from thousands of prior projects.
Question: What advice for other software leaders?
Don't implement AI just to satisfy board pressure.
Identify problems without mentioning generative AI first.
Innovation should come from listening to customers.
Question: Future plans with AWS partnership?
Moving toward automated remediation beyond just analysis.
Question: Has Sumo Logic monetized generative AI?
Changed pricing from data ingestion to data usage.
New model encourages more data sharing without cost barriers.

Participants:

Joe Kim – Chief Executive Officer, Sumo Logic

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

Ep086: Battling Fraud in the Age of Generative AI: Socure's Mission to Secure the Internet Mar 21, 2025

Show notes

CTO Arun Kumar discusses how Socure leverages AWS and generative AI to collect billions of data points each day in order to combat sophisticated online fraud at scale.

Topics Include:

Introduction of Arun Kumar, CTO of Socure
What does Socure specialize in?
KYC and anti-money laundering checks
Mission: eliminate 100% fraud on the internet
Fraud has increased since COVID
Socure blocks fraud at entry point
Works with top banks and government agencies
CTO responsibilities include product and engineering
Focus on increasing efficiency through technology
Two goals: internal efficiency and combating fraud
Countering tools like FraudGPT on dark web
Measuring success through reduced human capital needs
Fraud investigations reduced from hours to minutes
Improved success rates in uncovering fraud rings
Detecting multi-hop connections in fraud networks
Question: Who's winning - fraudsters or AI?
It's a constant "cat and mouse game"
Creating a fraud "red team" similar to cybersecurity
Partnership details with AWS
Amazon Bedrock provides multiple LLM options
Building world's largest identity graph with Neptune
Real-time suspicious activity detection
Blocking account takeovers through phone number changes
Success story: detecting deepfake across 3,000 IDs
Collecting hundreds of data points per identity
Challenges: adding selfie checks and liveness detection
Future strategy: 10x-100x performance improvements
Creating second and third-order intelligence signals
Internal efficiency applications of generative AI
AI-powered sales tools and legal document review

Participants:

Arun Kumar – Chief Technical Officer, Socure

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

Ep085: Securing the AI Frontier: Overcoming Security Risks featuring Oron Noah of Wiz Mar 19, 2025

Show notes

Oron Noah of Wiz outlines how organizations evolve their security practices to address new vulnerabilities in AI systems through improved visibility, risk assessment, and pipeline protection.

Topics Include:

Introduction of Oron Noah, VP at Wiz.
Wiz: largest private service security company.
$1.9 billion raised from leading VCs.
45% of Fortune 100 use Wiz.
Wiz scans 60+ Amazon native services.
Cloud introduced visibility challenges.
Cloud created risk prioritization issues.
Security ownership shifted from CISOs to everyone.
Wiz offers a unified security platform.
Three pillars: Wiz Cloud, Code, and Defend.
Wiz democratizes cloud security for all teams.
Security Graph uses Amazon Neptune.
Wiz has 150+ available integrations.
Risk analysis connects to cloud environments.
Wiz identifies critical attack paths.
AI assists in security graph searches.
AI helps with remediation scripts.
AI introduces new security challenges.
70% of customers already use AI services.
AI security requires visibility, risk assessment, pipeline protection.
AI introduces risks like prompt injection.
Data poisoning can manipulate AI results.
Model vulnerabilities create attack vectors.
AI Security Posture Management (ASPM) introduced.
Four key questions for AI security.
AI pipelines resemble traditional cloud infrastructure.
Wiz researchers found real AI security vulnerabilities.
Wiz AI ASPM provides agentless visibility.
Supports major AI services (AWS, OpenAI, etc.).
Built-in rules detect AI service misconfigurations.

Participants:

Oron Noah – VP Product Extensibility & Partnerships, Wiz

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

Ep084: Accelerating ISV Modernization: SoftServe's Six-Month Success Formula Mar 17, 2025

Show notes

Ruslan Kusov of SoftServe presents how their Application Modernization Framework accelerates ISV modernization, assesses legacy code, and delivers modernized applications through platform engineering principles.

Topics Include:

Introduction of Ruslan Kusov, Cloud CoE Director at SoftServe
SoftServe builds code for top ISVs
Success case: accelerated security ISV modernization by six months
Healthcare tech company assessment: 1.6 million code lines in weeks
Business need: product development acceleration for competitive advantage
Business need: intelligent operations automation
Business need: ecosystem integration and "sizeification" to cloud
Business need: secure and compliant solutions
Business need: customer-centric platforms with personalized experiences
Business need: AWS marketplace integration
Distinguishing intentional from unintentional complexity
Platform engineering concept introduction
Self-service internal platforms for standardization
Applying platform engineering across teams (GenAI, CSO, etc.)
No one-size-fits-all approach to modernization
SAMP/SEMP framework introduction
Core components: EKS, ECS, or Lambda
Modular structure with interchangeable components
Case study: ISV switching from hardware to software products
Four-week MVP instead of planned ten weeks
Six-month full modernization versus planned twelve months
Assessment phase importance for business case development
Calculating cost of doing nothing during modernization decisions
Healthcare customer case: 1.6 million code lines assessed
Benefits: platform deployment in under 20 minutes
Benefits: 5x reduced assessment time
Benefits: 30% lower infrastructure costs
Benefits: 20% increased development productivity with GenAI
Integration with Amazon Q for developer productivity
Closing Q&A on security modernization and ongoing management

Participants:

Ruslan Kusov – Cloud CoE Director, Softserve

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

Ep083: Navigating the AWS Bedrock Journey: Planview's AI Evolution Mar 13, 2025

Show notes

Richard Sonnenblick and Lee Rehwinkel of Planview discuss their transition to Amazon Bedrock for a multi-agent AI system while sharing valuable implementation and user experience lessons.

Topics Include:

Introduction to Planview's 18-month journey creating an AI co-pilot.
Planview builds solutions for strategic portfolio and agile planning.
5,000+ companies with millions of users leverage Planview solutions.
Co-pilot vision: AI assistant sidebar across multiple applications.
RAG used to ingest customer success center documents.
Tracking product data, screens, charts, and tables.
Incorporating industry best practices and methodologies.
Can ingest customer-specific documents to understand company terminology.
Key benefit: Making every user a power user.
Key benefit: Saving time on tedious and redundant tasks.
Key benefit: De-risking initiatives through early risk identification.
Cost challenges: GPT-4 initially cost $60 per million tokens.
Cost now only $1.20 per million tokens.
Market evolution: AI features becoming table stakes.
Performance rubrics created for different personas and applications.
Multi-agent architecture provides technical and organizational scalability.
Initial implementation used Azure and GPT-4 models.
Migration to AWS Bedrock brought model choice benefits.
Bedrock allowed optimization across cost, benchmarking, and speed dimensions.
Added AWS guardrails and knowledge base capabilities.
Lesson #1: Users hate typing; provide clickable options.
Lesson #2: Users don't like waiting; optimize for speed.
Lesson #3: Users take time to trust AI; provide auditable answers.
Question about role-based access control and permissions.
Co-pilot uses user authentication to access application data.
Question about subscription pricing for AI features.
Need to educate customers about AI's value proposition.
Question about reasoning modes and timing expectations.
Showing users the work process makes waiting more tolerable.

Participants:

Richard Sonnenblick - Chief Data Scientist, Planview
Lee Rehwinkel – Principal Data Scientist, Planview

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

Ep082: Accelerating Profitable Growth with SaaS with DataRobot, LaunchDarkly and ServiceNow Mar 11, 2025

Show notes

Executives from DataRobot, LaunchDarkly and ServiceNow share strategies, actions and recommendations to achieve profitable growth in today's competitive SaaS landscape.

Topics Include:

Introduction of panelists from DataRobot, LaunchDarkly & ServiceNow
ServiceNow's journey from service management to workflow orchestration platform.
DataRobot's evolution as comprehensive AI platform before AI boom.
LaunchDarkly's focus on helping teams decouple release from deploy.
Rule of 40: balancing revenue growth and profit margin.
ServiceNow exceeding standards with Rule of 50-60 approach.
Vertical markets expansion as key strategy for sustainable growth.
AWS Marketplace enabling largest-ever deal for ServiceNow.
R&D investment effectiveness through experimentation and feature management.
Developer efficiency as driver of profitable SaaS growth.
Competition through data-driven decisions rather than guesswork.
Speed and iteration frequency determining competitive advantage in SaaS.
Balancing innovation with early customer adoption for AI products.
Product managers should adopt revenue goals and variable compensation.
Product-led growth versus sales-led motion: strategies and frictions.
Sales-led growth optimized for enterprise; PLG for practitioners.
Marketplace-led growth as complementary go-to-market strategy.
Customer acquisition cost (CAC) as primary driver of margin erosion.
Pricing and packaging philosophy: platform versus consumption models.
Value realization must precede pricing and packaging discussions.
Good-better-best pricing model used by LaunchDarkly.
Security as foundation of trust in software delivery.
LaunchDarkly's Guardian Edition for high-risk software release scenarios.
Security for regulated industries through public cloud partnerships.
GenAI security: benchmarks, tests, and governance to prevent issues.
M&A strategy: ServiceNow's 33 acquisitions for features, not revenue.
Replatforming acquisitions into core architecture for consistent experience.
Balancing technology integration with people aspects during acquisitions.
Trends in buying groups: AI budgets and tool consolidation.
Implementing revenue goals in product teams for new initiatives.

Participants:

Prajakta Damle – Head of Product / SVP of Product, DataRobot
Claire Vo – Chief Product & Technology Officer, LaunchDarkly
Anshuman Didwania – VP/GM, Hyperscalers Business Group, ServiceNow
Akshay Patel – Global SaaS Strategist, 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/

Ep081: Customer-First AI: DTEX Systems’ Journey with Generative AI and AWS Mar 04, 2025

Show notes

Ryan Steeb shares DTEX Systems’ strategic approach to implementing generative AI with AWS Bedrock, reducing risk while focusing on meaningful customer outcomes.

Topics Include:

Introduction of Ryan Steeb, Head of Product at DTEX Systems
Explanation of insider risk challenges
Three categories of insider risk (malicious, negligent, compromised)
How DTEX Systems is using generative AI
Collection of proprietary data to map human behavior on networks
Three key areas leveraging Gen AI: customer value, services acceleration, operations
How partnership with AWS has impacted DTEX's AI capabilities
Value of AWS expertise for discovering AI possibilities
AWS Bedrock providing flexibility in AI implementation
Collaboration on unique applications beyond conventional chat assistants
AWS OpenSearch as a foundational component
Creating invisible AI workflows that simplify user experiences
The path to monetization for generative AI
Three approaches: direct pricing, service efficiency, operational improvements
Second and third-order effects (retention, NPS, reduced churn)
How DTEX prioritizes Gen AI projects
Starting with customer problems vs. finding problems for AI solutions
Business impact prioritization framework
Technical capability considerations
Benefits of moving AI solutions to AWS Bedrock
Fostering a culture of experimentation and innovation
Adopting Amazon's "working backwards" philosophy
Balancing customer-driven evolution with original innovation
Time machine advice: start experimenting with Gen AI earlier
Importance of leveraging peer groups and experts
Future outlook: concerns about innovation outpacing risk mitigation
Security implications of Gen AI adoption
Participation in the OpenSearch Linux Foundation initiative
Final thoughts on the DTEX-AWS partnership

Participants:

Ryan Steeb – Head of Product, DTEX Systems

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

Ep080: When AI Meets Accounting - How Sage is Transforming Business Software Feb 25, 2025

Show notes

From cost management to practical implementation, Sage's Amaya Souarez shares invaluable insights on building AI-powered business tools that deliver measurable value to customers.

Topics Include:

Amaya Souarez introduced as EVP Cloud Services at Sage
Overview of Sage: offers accounting, finance, HR and payroll tech for small businesses
Company emphasizes human values alongside technology development
Amaya oversees core cloud services and operations across 200+ products
Sage Co-Pilot announced as new AI assistant – helping automate invoicing and cash flow management
Common misconceptions with Generative AI
AI solutions aren’t always solution to every problem
Compares AI hype to previous blockchain enthusiasm
Emphasizes starting with clear use cases before implementation
Difference between task-based and reporting-based use cases
Partnering with AWS to build accounting-specific language models
Different accounting terminology varies by country
Using AWS Bedrock and Lex for a domain-specific language model development
Multiple AI models may be needed for single solution
Customer feedback drives project funding decisions
AI development integrated into regular product roadmaps
Focus on reducing cost per user for AI features
Success story: reducing 20-hour task to 5 minutes
Tracks AI usage costs per customer interaction
Early Gen AI hype caused confusion in the market
Plans to make domain-specific models available via API
Will offer language models on AWS Marketplace
Emphasizes practical AI application over blind implementation

Participants:

Amaya Souarez - EVP Cloud Services and Operations, Sage

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

Ep079: AI, Innovation, and the Enterprise: Box's Journey with AWS Feb 18, 2025

Show notes

Box's Chief Product Officer Diego Dugatkin discusses how the enterprise content management platform is leveraging AI through partnerships with AWS Bedrock and continuing to innovate for their customers.

Topics Include:

Introduction of Diego Dugatkin as Box's Chief Product Officer
Box provides cloud content management for enterprise customers
Focus on Intelligent Content Management
Box serves 115,000 customers including 70% of Fortune 500
Company manages approximately one exabyte of enterprise data
Box expanding product portfolio to offer more customer value
Partnership with AWS Bedrock for AI implementation announced
Collaboration with Anthropic for LLM technology integration
Box offers neutral approach letting customers choose preferred LLMs
Common misconceptions about generative AI capabilities and limitations
Generative AI helps accelerate contract analysis and classification processes
Box Hubs enables content curation and multi-document queries
Success measured through hub creation and query accuracy metrics
Long-term AWS partnership continues expanding with new technologies
Amazon is major Box customer while Box uses AWS
API integration important for third-party developer implementations
AI development exceeding speed expectations in efficiency improvements
Challenges remain in defining AI agent roles and capabilities
Content strategy crucial for deploying intelligent content management
Companies must prepare for AI agents in workplace
Flexibility in tech stack recommended over single-vendor approach
Next 12-24 months will see accelerated industry changes
Box maintains innovative culture through intrapreneurship approach
Company regularly hosts internal and external hackathons
Focus on maintaining integrated platform while acquiring companies
Partnership between Box and AWS continues growing stronger

Participants:

Diego Dugatkin – Chief Product Officer, Box

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

Ep078: Scaling Through Partnerships: Snowflake's Cloud Engineering Success Feb 11, 2025

Show notes

Through case studies of Graviton implementation and GPU integration, Justin Fitzhugh, Snowflake’s VP of Engineering, demonstrates how cloud-native architecture combined with strategic partnerships can drive technical innovation and build business value.

Topics Include: