Priyanka Vergadia hops back into the host seat this week, joining Mark Mirchandani to talk to Marit Rødevand of Strise. Strise is an AI-driven enterprise company using knowledge graphs to gather and analyze massive amounts of information, depositing it into a web-based interface to help large clients such as banks solve data-driven problems. Strise’s web-based data platform is customizable, flexible, and capable of keeping up with the fast-paced world of technology so enterprise companies aren’t constantly putting time and resources into reworking old or building new software. To do this, Strise uses knowledge graphs rather than typical databases to create what Marit calls a future-proof data model.

Marit explains knowledge graphs in detail, emphasizing that they can reduce training of machine models, allow new data to be input easily, and make analyzing unstructured data much easier. Knowledge graphs take data that would normally only make sense to humans and in effect translate it for computers. Using banking as an example, she details how information about customers can be collected and analyzed thoroughly to help the bank come to conclusions about credit-worthiness or possible criminal activity.

On Strise’s platform, Marit tells us that the information is now available to the end user who provides feedback to the system, marking things as relevant or irrelevant, rather than leaving those decisions to a data scientist outside of the client’s field. This means that massive amounts of information could be stored in the knowledge graph, across many industries, and each user only gets the data he or she needs.

Google Cloud tools such as Kubernetes Engine, Dataproc, and Pub/Sub have played an integral roll in the creation of the Strise data pipeline. Marit explains how Strise gets their data, how it’s input into the knowledge graph, and how these Google tools help to keep Strise running.



Marit Rødevand

Marit Rødevand is the CEO & co-founder of Strise, an AI startup from Norway who is signaling a new era of enterprise software.

Strise makes the world’s information useful across the enterprise. Their novel approach by utilizing a knowledge graph to power their data platform, allows Strise to break data silos, end customization projects, and bring new insights from unstructured data. Strise is currently helping leading Nordic banks and financial institutions to solve their hardest data-driven problems within KYC/AML, risk, and sales.

Strise recently announced their Seed round from Maki.vc, the leading Nordic early stage investor, who invests in deep tech & brand-led startups.

Marit has a background from Cybernetics & Robotics at the Norwegian University of Science and Technology (NTNU). In university, she co-founded Rendra, a construction SaaS, who was later acquired. Marit started as Entrepreneur in Residence at NTNU where she spun Strise out of a research project that focused on new data models as a foundation for better AI.

Cool things of the week


BakeML site


David East’s Firebase Podcast podcast

Automating BigQuery exports to an email blog
Cloud OnBoard site


Interview


Strise site
A world in text — Strise blog
GKE site
Helm sote
Dataproc site
Operations site
Cloud Run site
Cloud Pub/Sub site
Cloud DNS site
Cloud Storage site
GCP Podcast Episode 198: SeMI Technologies with Laura Ham podcast
Building on Google Cloud with SeMI Technologies - Stack Chat video
Knowledge graphs with Weaviate - Stack Chat video
Natural Language Data Processing with Mito.ai - Stack Chat video


Question of the week

Zach answers the question “What’s a cool thing in Cloud that many people may not have thought about?” GSuite and Apps Script

What’s something cool you’re working on?

Priyanka wrote this post on 13 Most Common Google Cloud Reference Architectures and her parents were on the news for the vegetable garden they’ve been working on. She’s also been working with material design components and firebase hosting.
And The Data Sh