Build Scalable SaaS Product Portfolios – the Right Way!
Updated May 11, 2026
Summarize in ChatGPTLow code/no code solutions? Unscalable? Inefficient? No more. Watch the video featuring Boaz Brudner, Head of Innovyze SaaS engineering, to learn why you should pay attention to these technologies and SaaS project management. The presentation was made at the Glorium Technologies virtual summit.
Topic – Build Scalable SaaS Product Portfolios – the Right Way!
- Agile development from an executive leader’s perspective – how to be agile and fast in the short term and at the same time create a predictable long term roadmap and vision for the company and your customers.
- Focus on building customer value vs building infrastructure.
- The rise of serverless for SaaS, big data and AI and why you should pay attention.
- Future trends to lookout for in the low code/ no code SaaS, AI and big data spaces
About speaker
Boaz Brudner is the head of Innovyze SaaS engineering, AI and architecture ( Innovyze was recently acquired by Autodesk). Boaz joined Innovyze early on in 2020 to champion Innovyze’s transformation from a desktop based water software provider to a leader in the SaaS and AI products for water professionals. This transformation has been nothing short of remarkable, within 8 months of development kick off Innovyze released its first full scale SaaS product named Info360 Insight to market and has released 2 additional products since then in very short timelines of 6-8 months. These achievements were achieved by building a remarkable set of teams, setting a well defined agile development process, relying on bleeding edge managed and serverless cloud services, highly decoupled event driven architecture and uncompromising customer value prioritisation. Prior to this role, Boaz held a number of senior leadership roles at Cisco and Zillow leading engineering, AI, QA and product management functions.
You can get the full recording of the virtual summit «Boosting SaaS products with new technologies. Big Data. Data Science. Artificial Intelligence. Machine Learning» here.
