The 14th cohort of NetApp’s Excellerator program is here. The program began in 2017 as an India-specific initiative catering to startups building solutions for the country. Today, the scope and ambition are bigger, with a mix of international and Indian startups building cutting-edge solutions in data, artificial intelligence and machine learning (AI/ML).
The program provides startups with resources, mentorship, as well as access to NetApp’s (cloud, hybrid cloud, AI and analytics) technology and its global network, allowing them to accelerate product development, refine business strategies, scale solutions, and reach new milestones.
In the last eight years, the program has empowered multiple startups and fostered innovation by engaging with 90+ startups out of which 22 were women-led ( 11 women-led startups mentored under NetApp ExcellerateHER), resulting in 29 pilots and 9 exits.
The 14th cohort features an array of exciting startups in the AI/ML and data space, with two started by Israel-origin founders, three by Indian-origin founders. Sentra, a cloud data security startup, has raised $112 million in Series B funding, while TrueFoundry, a startup that works in ML training and deployment, is working with companies like NVIDIA, CVS, Siemens Healthineers, and more on Proofs of Concept. From multimodal time series models to data compression and customized LLM deployment, this cohort is at the forefront of AI innovation.
Speaking on the launch of the cohort, Vasanthi Ramesh, Managing Director, NetApp India, said, “We’re excited to welcome and partner with startups that are building transformative solutions using advanced technologies. The maturity stage and the focus area of each of the participating startups reflect our ongoing commitment to innovation with AI. Through the program, we offer resources, mentorship, and technological expertise they need to scale. I am looking forward to the collaborative success and witnessing how these AI-focused startups will shape the future of tech on a global stage.“
Meet the five startups from the 14th cohort of NetApp Excellerator:
Genloop.ai: Enabling swift deployment of LLMs
Generic AI models find it hard to understand and operate within unique and complex environments of various industries. Lack of customization, a need for significant technical expertise and resources, and the necessity to build strong security and data privacy measures leave many organizations struggling. However, there is hope on the horizon, with customized large language models tailored to an organization’s requirements and that offer more accurate and contextual insights than generic models.
Genloop.ai’s platform allows for the rapid deployment of these LLMs, creating tailored AI solutions from proprietary data. This bootstrapped startup, founded by Ayush Gupta, ex-co-founder of Brance, is headquartered in California with the team ensuring everything from 100% data privacy as well as automated data cleaning. Genloop.ai’s platform supports both continuous learning of enterprise data and optimization of LLMs.
“Data is an enterprise’s most critical asset, one that must be securely understood and protected. That’s why we’re thrilled to be working with NetApp as a part of Netapp Excellerator. As a leader in intelligent data infrastructure, their focus on secure, enterprise-grade systems aligns perfectly with our mission: enabling organizations to build personalized GenAI systems that learn from their data and deliver insights with precision. We’re excited to learn, collaborate, and build alongside the NetApp team and fellow cohort members,” says Ayush Gupta, CEO, Genloop.
Businesses across various industries and sectors can leverage GenAI capabilities efficiently. The platform also assures clients of 5x cost savings, 10% better performance, 2x faster, and zero developer effort as existing models can be upgraded to more specialized versions without the need for heavy development resources. Genloop.ai is currently running product testing for Deutsche Telecom, and is in negotiations with organizations such as AT&T, Samsung, Schneider Electric, and InfoVista.
TrueFoundry: Building, deploying and managing ML/ LLM apps in minutes
Enterprises struggle to deploy, manage, and scale their ML and GenAI applications. This process can be slow and resource intensive, requiring heavy DevOps input and customized infrastructure. Furthermore, running complex AI workloads often turns out to be expensive and difficult to manage. Along with that, companies must also ensure strict data privacy, governance, and compliance when deploying these models.
This is where TrueFoundry comes in. This cloud-native Platform as a Service enables machine learning teams to build, deploy, and manage ML and LLM applications on their own cloud or on-premises infrastructure, saving them considerable time, effort, and money. Founded in 2021 by Anuraag Gutgutia, Abhishek Choudhary and Nikunj Bajaj and headquartered in California, USA, TrueFoundry enables teams to achieve a 90% faster time to value as opposed to traditional methods. The platform offers features such as rapid deployment (in as little as 15 minutes), robust data governance, and a suite of tools such as LLMOps, GenAI accelerators, and smooth integrations with popular frameworks. TrueFoundry has raised $21.3 million in Series A funding and has Nvidia, CVS, Merck, Siemens Healthineers and other Fortune 1000s on its client roster.
“We applied to the program because the program combines world-class technical mentorship with real pathways to global customers, letting us validate and harden our product in demanding environments. Over the next six months we’re excited to co-innovate with NetApp engineers, learn from their go-to-market leaders, and tap into the Excellerator alumni network. We believe this collaboration will accelerate our journey to make production ML frictionless for every company,” says Anuraag Gutgutia, COO, TrueFoundry.
Sentra: A sentry for cloud environment security
While public cloud environments offer flexibility and scalability, they can also introduce a range of security risks that organizations must address proactively to protect sensitive data, workloads and company reputation. Misconfiguration, data breaches, accidental data exposure, human error, increased attack surfaces, unsecured APIs, weak authentications – security risks run the gamut in public cloud environments.
Sentra, a global leader in cloud native security, leverages advanced ML techniques to autonomously classify structured and unstructured data, resulting in accurate identification as well as proper management of sensitive information across diverse environments – both cloud and on premises. By integrating data security posture management (DSPM), Data Access Governance (DAG) and Data Detection and Response (DGG), it provides a unified approach for organizations to assess risks, maintain access and deal with threats to sensitive data in real-time. This Series A startup was established in 2021 by Yoav Rogel, Ron Reiter, Yair Cohen and Asaf Kochan, and is headquartered in Tel Aviv, Israel. “As organizations rapidly adopt AI and cloud technologies, the need for intelligent, scalable, and privacy-first security has never been greater. Applying to the NetApp Accelerator is a strategic move for us, not just to scale innovation, but to collaborate with a leader that shares our vision of empowering enterprises through data. We see this program as an incredible opportunity to combine forces, deepen our technology, provide better solutions to our customers, and help global organizations safeguard what matters most: their data,” says Yoav Regev, CEO, Sentra.
Sentra has raised $100 million in Series B funding, and is partnering with papayaglobal, Placer.ai, Stackline, bigbasket, Healthcare Bluebook and others for Proof of Concept (POC).
Synthefy: Mining time series data for the right insights
Time series data – a sequence of data points collected or recorded at specific intervals in time (every minute, hour, day or month) – are typically chronological in nature and reflect how a variable changes over time. Used in statistical analysis or ML learning techniques to mine insights, it has applications in industries such as finance, weather forecasting, industrial equipment maintenance, sales tracking, and healthcare monitoring.
Synthefy, a startup founded in 2023 by Somi Agarwal, Shawn Jain, Dr. Sandeep Chinchali and Raimi Shah, develops advanced algorithms, neural networks, and deep learning models, such as the ‘world’s first foundation model for multimodal time series data’.
“With NetApp ingesting petabytes of time-series and telemetry data, it’s an ideal partner to showcase how Synthefy’s Time Series Foundation Models can scale, secure, and generate real-world value. We’ve already begun engaging with the team on exciting use cases and look forward to delivering tangible impact alongside NetApp’s experts” says Shubhankar Agarwal, CEO, Synthefy.
Synthefy’s GenAI technology allows enterprises to discover insights from their time series data. Its platform leverages unstructured data for forecasting, including on-prem forecasting models that are smaller and can run smoothly on single GPUs. With $6 million seed funding raised, Synthefy is currently undergoing production testing for Deutsche Telecom and is in contract discussions with AT&T, Samsung, Schneider Electric and InfoVista.
Filo Systems: Making data faster, smaller, and manageable
In the current digital landscape – awash with data – compression is vital. It dramatically reduces the amount of space required to store data, allowing organizations to store more within their cloud or physical infrastructure. Furthermore, decreasing storage costs has led to substantial cost savings. Data compression also enables organizations to transfer data speedily across networks, reduce bandwidth consumption and improve data management.
Filo Systems, a startup headquartered in Tel Aviv, and founded by Ofer Markman and Etamar Laron in 2022, specialises in data compression technology through its flagship data compression engine that reduces data size, improves download speeds, and enhances network efficiency. Its solutions have greatly enhanced the productivity of applications that require swift data processing and the efficient use of resources. With a total of $1.2 million raised through Series A funding, Filo Systems is in the process of completing five large pilots in Israel and Europe, and has completed POCs with Intel R&D, Ministries of Defense and Health in Israel, and the CS Research Centre.
“Filo Systems, the leader in Data Compression ratios, is participating in NetApp’s prestigious Excellerator program. Together, NetApp and Filo shall engage visionary customers interested in PoC over today’s densest object storage and distributed file-systems, for a variety of entry-level use-cases. Filo uniquely transitions the field of data-compression to AI-based information-compression. Entering Excellerator is the culmination of 7 years of research, development and product work to deliver today’s densest storage technology at the lowest cost. We are enthusiastic and grateful for the opportunity to work with NetApp, and add unprecedented capabilities to the market leader,” says Laron.
Guiding the Indian startup ecosystem
Over the years, NetApp has mentored 25 global startups through NetApp Excellerator and 11 women-led deeptech startups through NetApp ExcellerateHER. Their success can be measured through their alumni who have gone on to raise over $600 million collectively. There have also been successful exits by nine alumni startups. NetApp Excellerator was declared to be one of the top five accelerator programmes in India for corporate innovation by NexTT Awards. The award-winning program now includes a proof of concept (PoC) model that provides startups a platform to demonstrate the efficacy of their solutions in the real-world. They work in tandem with NetApp to refine their minimum viable products (MVPs), identify possibilities and additional use cases, which is then used to chalk out their go-to-market strategies.
