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NetSpring, a startup offering a platform to deliver AI-driven operational intelligence to enterprises, today announced it has raised $13 million in a series A round led by Dell Technologies Capital. The company plans to use the investment, which also saw the participation of Khosla Ventures and Wipro Ventures, toward strengthening its team and developing the infrastructure of its solution.
With rapid digitization, automation, instrumentation of digital experiences, and growth in the number of connected devices, organizations are facing an explosion of event data volumes — regardless of the sector. This freshly generated, raw, transaction-level data is immediately actionable and has the potential to inform various operational business decisions, improving the efficiency and profitability of any organization. However, companies often fail to take advantage of this opportunity; most traditional analytics systems run as an offline process on stale data, away from the fresh data streaming from day-to-day operations in real time.
The backward-looking approach delays the detection and remediation of immediate operational issues such as customer experience degradation (such as payment gateway slowdowns), API outages, risk exposure, or supply chain disruptions.
NetSpring’s AI-driven operational intelligence
Founded in 2019 by Vijay Ganesan, Priyendra Deshwal, Satyam Shekhar, and Abhishek Rai, NetSpring solves this challenge with a cloud-native platform that lives online where the data is created. The solution, working as a unified command center, integrates into the everyday operations of a business (transactional and collaboration applications) and uses AI/ML to generate continuous actionable insights from streaming event data-in-motion and static reference data-at-rest, enabling faster analytics and operational decision-making.
“NetSpring’s platform continuously processes every event in the system and proactively alerts users of anomalies and patterns of interest in data, in real time,” Ganesan, who is the CEO of NetSpring, told VentureBeat. “The platform also provides visual interfaces and advanced scripting interfaces, for diagnostics and causality analysis to quickly find the root cause of operational issues.”
Companies using NetSpring’s AI-driven solution can also run low-latency queries on streaming data and act on sudden business events with manual and automated corrective actions across external-facing applications and internal infrastructure.
“Whether it is continuous engagement with customers, dynamic supply-demand matching, optimizing product experiences, efficient risk management, dynamic pricing/promotions, or reacting to competitive events, NetSpring helps enterprises have a real-time pulse on their business operations — continuously and at scale,” Ganesan said.
Vendors like Databricks and Amplitude offer solutions along the same lines. However, NetSpring claims to differentiate itself as an integrated data and application platform, providing customers an end-to-end solution with a no-code application composition environment, advanced event flow, and dimensional slice-and-dice analytic capabilities for actionable business observability.
“We also offer a unique compute engine based on Converged Analytical Processing (CAP) technology, that is the first scalable converged streaming and batch query engine with integrated storage. This enables servicing a rich class of operational intelligence use cases that other systems cannot do today,” Ganesan added.
Moving forward, the company will focus on strengthening its engineering, including its SaaS infrastructure. It also plans to expand its sales and marketing teams to take the solution to more customers. It aims to have clients on the scale of dozens by the first half of 2022.
“We have a bold vision that some years from now if you look at the data analytics machinery at any major enterprise, you will see three key things powering a large class of core analytics workloads: a streaming pipe like Apache Kafka, a cloud data lake on stores like AWS S3, and the NetSpring Operational Intelligence Platform. We strongly believe that this will result in massive simplification, reduced cost, and increased analytic sophistication at enterprises, making a huge impact on business agility,” Ganesan said.
According to Gartner, AI augmentation will create $2.9 trillion of business value in 2021. By 2030, decision support/augmentation will surpass all other types of enterprise AI initiatives, accounting for 44% of the global AI-derived business value.
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