Dutch startup OPT/NET creates AI products for a variety of critical and data-intensive industries, but far from replacing humans, they want to make them superhuman with AI-assistance.
Tell us about your start up
At OPT/NET, we are a fresh entrant into the AIOPs industry. The complexity of IT systems is increasing exponentially. The users running these systems are struggling to keep up. Inevitably, mistakes are made, and costly outages occur. One day of downtime costs large enterprises over 7M$ per day. By leveraging AI, we empower network operators with intelligent data-driven insights so they have the full live picture of everything that’s happening within their networks. We ingest all of the network telemetry (logs, metrics, KPIs, etc) available to deliver real-time proactive intelligence on brewing issues in the network. Our goal is to find the issues before they impact the service and customers.
What is your USP?
We have 3 key technological differentiators:
Our patented AI approach can derive anomalous sequences of events and determine causality between events. This lets operators trace back the impact to the root causes far more efficiently than competing solutions.
Every network is different and no one-size fits all solution will properly work. We’ve built a modular “composable” AI architecture so that we can support any Customer’s IT landscape with “out of the box” capability.
Our approach requires no model training and works with raw data from day 1. The AI detects and clusters anomalous network activity, and we leave the conclusion-making to domain experts whose expertise is retained by the platform post-interpretation.
What is your relationship with the telecom sector?
The Telecom Sector is our primary market of interest. Our main Customers are large Network Operators (CSPs) and our product is best suited to IT-Infrastructure monitoring, making it a great fit for the Telecom industry.
How have you got to your current stage of development?
Our product first started as an Open Source Network management/discovery solution called NG-NETMS. This product was first launched in 2013 and has been downloaded over 200K times with positive reviews. Subsequently, we took part in the European Space Agency’s Technology Transfer program to start developing an AI module for our product by incorporating some of their space-worthy algorithms. Next, we collaborated with the AI institute of the University of Amsterdam (top 5 AI institute in Europe) to further advance our Machine Learning module. Finally, in 2018, we pivoted from a Consulting company to a product-based company to bring our new product: OptOSS AI to the market.
Why did you establish the business?
OPT/NET was founded in 2018 as a spin-off from OPT/NET Consulting to focus on bringing the product to the Telecom industry. The founding team considered that the technology that had been built was a more scalable that providing traditional consulting services. Now that we have several large Telcos using our product, we are glad we made the transition.
Who inspired you?
We were inspired by our own consultants. They were struggling to find solutions on the market that could assist them in their IT-Infra data analysis activities so we started developing internally to assist them. Now, we are inspired by our Customers who are glad about their choice of opting for OPT/NET and often show us how it helped them solve brewing issues in their IT-Infrastructure!
What does the future hold for your business?
We hope to continue to grow! To do so, we are aiming to raise 2M in equity financing. We have our first key customers who are extremely satisfied proving we have a product-market fit. We can continue to grow organically but aim to raise funding to aggressively invest in outbound sales to entrench ourselves in a strong position in Europe for the quickly growing AIOps industry
OPT/NET will participate in the Startup Village at the Total Telecom Congress, taking place at The RAI this November. If you would like your startup to join them, visit www.totaltele.com/congress for more information.