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NetApp Excellerator cohort 9: Demonstrating an agile approach to innovation with data, cloud, and AI

NetApp Excellerator cohort 9: Demonstrating an agile approach to innovation with data, cloud, and AI

Friday November 19, 2021 , 10 min Read

Gartner's strategic technology trends for 2020 has pointed at growing relevance and usage of data fabrics among other technologies such as AI, distributed enterprise, and security. A data fabric is a powerful architecture that standardises data management practices and practicalities across cloud, on premises, and edge devices. Among the many advantages that a data fabric affords, data visibility and insights, data access and control, data protection, and security quickly rise to the top.

According to NetApp — a company that has pioneered and championed data fabric — a data fabric is, at its heart, an integrated data architecture that’s adaptive, flexible, and secure, and in many ways the new strategic approach that unlocks the best of cloud, core, and edge for enterprise storage operation.

What stands out about data fabric is that it is not only built upon a rich set of data management capabilities that ensure consistency across a business integrated environment, but can also reach anywhere, including on premises, public and private clouds, and edge and IoT devices, while remaining centrally governed. With the data fabric, businesses can now monitor storage costs, performance, and efficiency and also the “who is using what and how”— regardless of where the data and applications live. This then translates into actionable insights into the business’ hybrid cloud environment which then can be leveraged to remediate problems, address security and compliance risks, or dialing up and down compute.

“Over the years, we have witnessed how a data fabric designed for simplicity and agility can help to monetise data and hybrid cloud to meet business demands at speed,” says Madhurima Agarwal, Director of Engineering Programmes, and leader of NetApp Excellerator. She adds, the relevance of data fabric hasn’t been felt more than it is today to put data to work. Startups echo the sentiments. “While data being the new oil is cited enough, it is true. And, so it has become critical for businesses to tap into this gold mine,” shares Puneet Badrinath, Founder, Fabrik, an immersive technology company using AR/VR capabilities to solve engineering and lifecycle management related challenges for enterprises. Its next generation data and knowledge visualisation platform is reimagining the way individuals and enterprises interact with data and knowledge collaboratively in real-time. Mousumi Kapoor, Founder & CEO, Continual Engine, AI-driven startup, shares, “Our customers use our cloud-based solutions extensively with critical-to-business data and documents. Building a data fabric is absolutely vital and at Continual Engine, we have invested in an API-first cloud architecture that provides transparency and insights to our customers, while ensuring data privacy and security.” Startup founders reiterate that being data-driven today is not about competitiveness but growing sustainably by solving core business and technology challenges.

Fabrik and Continual Engine are among the eight startups that have been selected for NetApp Excellerator cohort 9 and NetAppExcellerateHER cohort 3 respectively. While Excellerator is NetApp’s global programme for startups, ExcellerateHER is NetApp’s dedicated accelerator program that supports women entrepreneurs disrupting the technology space. “The startups which are a part of NetApp Excellerator cohort 9 are solving diverse business challenges across sectors by reimagining data usage and integration. And, by doing so, they are demonstrating the future of data-driven, cloud-led, innovation,” shares Madhurima.

NetApp Accelerator Cohort 9: Emerging tech innovation with data, hybrid cloud and AI

Here’s a quick look at the eight startups

  • Fabrik | 2018 | Bengaluru | Puneet Badrinath

There is a huge knowledge gap between the assembly line technicians and the supervisors due to the unavailability of a system that detects faults intuitively. This calls for the need for a solution that can detect the faults, present information in a simpler way, and enable seamless collaboration. Fabrik digitises the work processes and provides right information to the assembly line technicians in the form of digital work instructions and digital twins of the high value assets. It bridges the knowledge gap by providing step by step sequenced instructions intuitively. Experts can collaborate with the on-floor technicians with annotations which reduces downtime and faults. “Fabrik is a next generation of data and knowledge visualisation technology which takes the 3D-first approach and is reimagining the way individuals, and enterprises interact with data and knowledge collaboratively in real-time,” says Puneet.

  • NeuroPixel.AI | 2020 | Bengaluru | Arvind Nair and Amritendu Mukherjee

One of the most repetitive and operationally intensive processes that every fashion e-commerce player undertakes daily is the process of cataloging their apparel. It typically involves models, photographers, stylists, make-up artists, and post-production touch-up artists for each shoot. “We are building a Deep Neural Net framework that understands how apparel gets deformed when worn by models of different sizes in different poses. With this, we will enable our clients to shoot any apparel on just a mannequin, and generate high resolution catalog images on the fly with models wearing those clothes in a variety of poses,” says Arvind, the CEO. The solution promises to bring down cataloging costs by 30 percent and process times by 90 percent. “What we're most excited about is that it can usher in an era of catalog-based personalisation where customers can view any apparel on a model of a similar ethnicity and a similar size as theirs, thereby driving higher conversion and revenues for any platform that deploys this,” he adds.

  • Datamotive | 2021| Pune | Yogesh Anyapanawar

Today, three out of five CIOs have a hybrid, multi-cloud strategy as part of their transformation roadmap. CIOs adopt this strategy in part to get the benefits of public cloud economics and in part to mitigate single-vendor risks. While this strategy has its merits, the dependency on these private or public platforms leads to the long-time ask from the CIOs for a true workload mobility solution that eliminates technology lock-ins, explains Yogesh, the founder of Datamotive.

Datamotive solves this very specific and critical problem for CIOs by providing freedom from platform lock-ins. Datamotive is the industry's first workload mobility solution enabling seamless recovery and migration of workloads from and between private and public clouds. Built ground up for high data volumes, in high latency networks, Datamotive provides enterprises with a guaranteed 10-minute Recovery/Cutover Time Objective (RTO/CTO) regardless of the workload size. With an agentless model, it treats the workloads as a complete black box, leading to improved security, management, and intrinsically enabling protection for any legacy or modern application.

  • NetObjex | 2015 | California | Raghu Bala

Businesses have various types of assets that need to be tracked, traced, monitored, and monetised in the new digital economy. NetObjex' Matrix Digital Asset as-a Service (DAaaS) platform enables enterprises to harness the power of IoT, AI, and blockchain technologies for managing digital assets across various industry verticals including smart cities, supply chain, and media. The Matrix platform is a low-code system, offering user-friendly tools with easy onboarding for enterprise clients. It includes five services -- Neo - a digital twin platform; Artemis - NFT storefront and marketplaces Trinity - A payment, tokenisation and DEX engine; Authentify - authentication for physical assets and TruDocs - a parametric contract engine. These services enable enterprises to perform several functions with assets such as unlock liquidity, detect counterfeit goods, enable monetization through storefronts and marketplaces, parameterise legal contracts, and track/trace/monitor using digital twins. Matrix is currently in use across four continents reaching 20M end users powering solutions in multiple industries.

  • Spectrum Analytics | 2017 | Gaborone (Botswana) | Tebogo Mogaleemang

Spectrum Analytics is a data innovation startup under Botswana Innovation Hub’s FSVC programme. The startup helps organisations use data to drive operational improvements and make evidence-based decisions. “We enable organisations to adapt and thrive in the digital economy by leveraging data and emerging technologies to start, accelerate, and sustain their digital transformation,” shares Tebogo, the founder. The startup provides solutions in the areas of application development, process innovation, data analytics, and cybersecurity.

  • FireVisor Systems | 2018 | Singapore | Surbhi Krishna Singh and Long Hoang

Manufacturing companies lose 15-30 percent of sales revenue due to cost of poor quality (COPQ). In fact, solar manufacturing loses 10B USD every year, and semiconductor loses 55B USD every year because of COPQ. Saving this cost could transform marginally successful companies into highly profitable ones. But understanding the root cause of every defect takes engineering data analysis which can get challenging with immense amounts of data being generated from different manufacturing systems. FireVisor provides AI-powered defect detection and analytics platforms that understand manufacturers’ data to reduce product failure and improve productivity. “Our goal is to predict defects even before they happen,” says Surbhi, the co-founder and CEO. She explains that ML Defect Detection platform catches all engineering defects automatically with very high accuracy and then automates the entire process of engineering data collection, cleaning, and analysis. “Our Defect Analytics platform connects to all types of data sources on the production floor, including image data, and performs the analysis in real-time. This saves engineers 37-50 percent of the time and enables defect root cause analysis much faster,” she says. Today, FireVisor’s AI system is being further developed to enable root cause prediction.

  • | 2021 | Toronto | Ruby Singh and Sanjay Arora

Ratings and reviews directly correlate to revenues online. But the sheer volume of unstructured e-commerce reviews makes it virtually impossible for brands to unlock and synthesise actionable insights across marketplaces without advanced AI.’s deep learning NLP platform monitors the voice of customers via unstructured product reviews and transforms them into actionable insights for brands and about their products, customers, and competitive landscape. “With the platform, we are able to provide insights down to the SKU and attribute level for our e-commerce clients which enables them to take meaningful action,” shares Ruby, the co-founder.

  • Continual Engine | 2017 | Texas & Bangalore | Mousumi Kapoor

Industry data suggests that nearly 217 million people in the world have moderate to severe vision impairment and 826 million live with near-vision impairment. As a result, they face severe "accessibility" challenges and are often compelled to drop out of traditional learning curriculums. The problem is even more compounded because educational institutions and corporations find it cumbersome and expensive to make their content and programmes accessible. Continual Engine is trying to solve this problem, by automating the process of making content accessible using AI. By using techniques like deep tech, computer vision, and neural nets, Continual Engine is able to perform the same task at half the cost in half the time, with greater consistency and higher quality, thereby enabling publishers and universities to make more content accessible which then levels the learning field for the differently-abled. Continual Engine’s cloud-based products - Invicta™ and PREP - are transformative solutions available globally both as a subscription (SaaS) and as services as well. Invicta is a Vision AI product that can analyse and describe STEM and tabular images and PREP automates the tagging of documents, including those with complex content such as tables or math equations, thus making them accessible for people with disabilities.