Meet Cohort 3 of the HPE Digital Catalyst Program

Hewlett Packard Enterprise (HPE) is back with its annual report HPE Digital Catalyst Program for its third edition to highlight innovations from India’s vibrant startup ecosystem. The goal of the program was to identify, co-innovate and commercialize the next generation of digital disruptors.

Over the past two years, HPE has worked with 14 startups across two cohorts, combining their expertise with the energy and innovation of new-age startups. This time they received over 150 entries, the jury saw and judged the pitches of the top 20 startups and chose their final seven startups. These startups will have access to HPE’s business and technology mentors, investor networks, and work closely with teams on go-to-market strategies and rapid prototyping.

Speaking of the program, Cynthia S Srinivas, VP – Software Engineering, Compute Business Group; The Indian Site R&D Manager at Hewlett Packard Enterprise said:

As we welcome the 3rd Cohort of startups to HPE Digital Catalyst Program, we are very excited about the opportunities for co-innovation with this diverse group working at the cutting edge of technology in areas such as AI, data science and the intelligent edge. As the program matures, we are seeing stronger commitment from our business units and sales teams, which I am sure will lead to more partnerships, joint solutions and GTM achievements.

Here is an overview of the current cohort:


With the aim of providing innovative and high value-added digital technology solutions for operations excellence, Syook offers a codeless IoT platform Syook InSite. InSite is a hardware- and cloud-independent, modular and fully configurable (no code) RTLS (Real Time Location System) platform.


SandLogic is a full-stack enterprise AI company that enables low-code, no-code (LCNC) platforms to enable deep learning applications to run on Edge devices. EdgeMatrix is ​​powered by its proprietary CORE porting and optimization engine and Deep Learning Accelerator (DLA). CORE helps port DNNs (Deep Neural Networks) to any Edge hardware like GPU powered devices like Jetson devices or Coral Sticks. The DLA converts non-GPU-based devices, systems, and SoCs into AI-enabled devices, to run neural networks for inference.


InfinStor is the AI ​​engine for unstructured data, allowing users to manage unstructured data and parallelize unstructured data computation. The software supports the full lifecycle of AI projects, from experiment tracking, model management, data management to calculation management. It allows AI workloads to be distributed between cloud resources and on-premises Kubernetes such as HPE Greenlake.


A powerful self-service data science and advanced analytics studio, Sparkflows seamlessly connects data from a wide variety of data stores, cleanses it, enriches it, and prepares it. It creates best-in-class machine learning models using the machine learning library of your choice. It allows you to seamlessly build analytical applications. It scales to petabytes of data and pushes analytics to the cluster of your choice.

Signzy Technologies

Signzy is a leading provider of digital banking infrastructure, whose GO platform delivers seamless, end-to-end, multi-product user journeys. It is not an AI-based, highly configurable, code-infused platform that offers rapid deployment. With over 200 customers, Signzy gives customers access to an aggregated marketplace of over 240 APIs that can be easily added to any workflow with simple widgets.

N5 Technology

N5 makes it easy to develop and run fintech and financial trading applications on bare metal and cloud. The N5 Rumi™ platform provides a complete and robust, high-performance, nanosecond latency, fully fault-tolerant infrastructure substrate for these applications, and N5 RumiCloud™ provides a state-of-the-art cloud platform co-located on the bare metal and exchange to run these financial applications in the cloud.


RocketML is a scientific machine learning platform for accelerating “time to solution” in many scientific applications through the use of AI methods. It provides companies with all the features needed to solve their engineering problems with machine learning. The product enables customers to scale machine learning models without limits, reducing development cycle times, personnel and material costs.

Ryan H. Bowman