Edge Executive Insight – Niranjan Maka, CEO & Co-founder, Smarthub AI – Edge StartUp of the Year FINALIST
In the lead up to Edge Computing World, we’re taking some time to speak to key Executives from the leading companies. Today we’re talking with Niranjan Maka, CEO & Co-founder of Smarthub AI
Tell us a bit about yourself – what led you to get involved in the edge computing market and Smarthub AI
I am Niranjan Maka, CEO SmartHub.ai. SmartHub.ai is based out of Bay Area, CA with offices in Seattle and Bangalore. My past experiences include holding global leadership positions for companies such as VMware, Siebel/Oracle, RSA Security, and TCS. Have also successfully launched companies in the past (that got acquired). I used to head the Edge Platform in VMware before it was spun out as SmartHub.ai
At VMware, I closely watched how the whole virtualization technology brought about innovation & disruption to the market, especially data centers and how it became a big movement behind cloud computing, for on-demand machine provisioning. A couple of years ago, also started noticing the pendulum swing towards edge computing. Computing happening right at the edge, where data is produced – both in enterprises and consumer side. It became clear that this was the new frontier where edge computing was going to have a profound impact on next level of innovation – especially around AI & 5G etc.,. This is what got me excited, and we quickly got behind Edge computing.
As companies accelerated their digital transformation & AI initiatives, a lot of the intelligent compute, workloads and data processing will happen right at the "EDGE", where this data is produced. Edge computing is important because it creates new and improved ways for industrial and enterprise-level businesses to maximize operational efficiency, improve performance and safety, automate all core business processes, and ensure “always on” availability. On the consumer side, it is the experiences (and new business models) that became the driver for edge computing.
In enterprises, as the footprint for edge experiences & infrastructure increase, the complexity of monitoring, managing and securing the components at the edge (Edge Endpoints/IoT endpoints) also increases, alongside the need to keep this edge infrastructure up and running, since this directly impacts the uptime/downtime of operations. The operations budget or team sizes is not going to increase proportionally, but the complexity is growing exponentially. Which means there is a need for modern tools and platforms to manage, monitor, secure and leverage this heterogenous and siloed infrastructure and rich data to learn to detect and learn new patterns and use this knowledge to tweak the environment for a better, richer, and secure experience. This is where SmartHub.ai comes into picture.
What is it you & your company are uniquely bringing to the edge market?
Today, enterprises can seamlessly monitor & manage their IT infrastructure (laptops, desktops, etc) and to a large degree manage their mobile devices as well (through MDM solutions). Where they still struggle (larger the company, bigger is their struggle) is to monitor & manage their edge infrastructure (especially heterogenous endpoints from many OEMs, which use different protocols and OS). They don’t have a unified way of managing this and the data coming from this edge siloed systems.
This is where our platform (SmartHub INFER™) makes it easy for enterprises to quickly have visibility into all their Edge infrastructure, monitor, manage and secure it – across groups/business units and operations. Once this is done, through our AI/ML modules, we offer rich ways of tapping into this edge data to drive actionable insights, automation and loopback learning systems to increase their uptime & operational efficiency. Most solutions in the market today are either very siloed & narrow in solving very specific use cases or focused on specific verticals.
What our Fortune customers love about SmartHub.ai is:
• The ability to "read" a complex, heterogeneous edge environment with different types of edge
devices, different vendors – provide an abstraction to get the data, performance characteristics,
and ability to send commands in bulk, detect and change configuration settings at scale.
• A modern workload enterprise / carrier grade platform built to the highest standards that
enterprise Infosec teams expect – thanks to the roots of founders in companies like Microsoft,
EMC, RSA Security and VMware. And the fact this platform has seen huge investments from
some of the best engineering from VMware
• One of the fastest time to deploy and ROI in the industry – We can get customers up and
running within days and not months. For every $1 USD spent on licensing, we help customers
achieve an ROI of $4.2 USD through savings in labor costs, automation, maintenance,
productivity increase, operational efficiency & risk mitigation (compliance, liabilities & breach)
Tell us more about the company, what’s your advantages compared to others on the market, who is involved, and what are your major milestones so far?
This is one of the few startups that has turned profitable within 12 months of coming out of stealth.
We launched in the middle of pandemic and all the growth happened through remote sales &
remote onboarding of customers onto our platform
• Marquee Fortune Global customers who are in production. We have two of the largest hyper-scalers
as our customers & other brands who are leaders in their space. Landed multi-year deals and 2 of
them are ~$2m+ deals
• Unique platform which helps companies roll it out once and leverage the same platform
across operations and business units.
• By the end of FY 2022 (Dec 2022), our revenue (bookings) would be at 200x compared to the
revenue from 2021
How do you see the edge market developing over the next few years?
We see the edge market, from a SmartHub.ai perspective rapidly evolve along two axes:
• Edge Devices Management/Unified Endpoint Management for Edge that includes the entire
Edge Device Lifecycle Management (Discovery, Monitoring, Managing, Securing & EOL), and
• Edge Data Management & Analytics (including AI / ML Ops)
Both are huge markets, totaling $80B and growing rapidly
What are the main trends you see about integrating edge computing into different verticals?
At SmartHub.ai, we look at trends with two lenses:
• 1-2 Year Horizon
o Edge Computing & Strategy becomes mainstream as part of Digital transformation
initiatives – Every company that is serious about being agile and competitive, have
realized that Edge computing is integral part of their Digital transformation vision and it
vastly impacts increases their top & bottom line growth.
o UEM for Enterprise Edge (Unified Endpoint Monitoring & Management) – Enterprises
have solved UEM for IT managed endpoints/devices (laptops, desktops, etc) and MDM
(Mobile Device Management). However, they don’t have capabilities yet for monitoring
and managing their far edge infrastructure cohesively. This vastly impacts their ability to
monitor & manage (secure, patch, control) their heterogeneous edge infrastructure.
Makes this infrastructure risky to vulnerabilities and malicious attacks as well. End-to-end
Edge/IoT Device Lifecycle Management is becoming important to large enterprises –
Visibility, Monitor, Manage, Secure & EOL (End-of-Life)
1. Deep Learning/AI/ML for Edge Data: With forecasts that by 2025, 75% of enterprise
generated data will be created and produced outside the data center or cloud,
enterprises have realized that they are sitting on a gold mine of data coming from
their edge…however most of it is siloed. Tapping into this to gain insights on their
business, enhance their abilities to server their customers better & improve their
operational efficiencies is already showing promise and tangible impact to their EBIT
2. AI workloads @Edge: Use cases around Low-latency, high throughput computing &
actions are rapidly being adopted at the edge (example: Safety,
Intrusions/Vulnerabilities, checkout-free retail). This requires H/W, S/W &
Infrastructure to be able to support this & is driving innovation in various categories.
Ability to train models & learnings in the cloud & push those learnt models to the
edge is gaining traction.
1. Vision based analytics – Intrusion detection, Object identification, checkout-free
retail experiences, behavioral analytics, etc are all part of new wave of analytics at
the edge, which allows companies to sense & respond at the edge
2. Predictive Analytics & Preventative Maintenance – While this has been talked
about in the past, there is more adoption in 2022 as companies look at preventing
expensive downtimes, predicting failure points and supporting their
infrastructure/operations with minimal resources
o Edge Compliance – Enterprises are going through an explosive growth in # of IoT
endpoints/devices within their infrastructure – often siloed and unmanaged. The number
of these devices are as high as 4-5x, the number of employees & this infrastructure is
larger than their IT managed footprint. So CISOs, business units using IoT based solutions
are under scrutiny by their compliance teams to monitor, manage and secure such infrastructure. In many cases, this is being looked at from potential liability risks as well.
We anticipate pressure from compliance teams to increase more and more and have
policies, procedures and processes in place for their IoT/Edge infrastructure in 2022 &
Growth of Edge/IoT devices in Enterprises: Operational teams and business teams will
continue embracing solutions driven by IOT to solve their specific use cases. H/W has
become extremely affordable, so it is easier for companies to embrace IoT driven
solutions and quickly realize tangible ROI
o Evolving Workplaces/Spaces: COVID has changed the landscape for workplaces
completely. Companies now are looking at supporting both traditional office places vs.
hybrid workplaces (including more satellite offices). Expectations of enhanced employee
experiences (often driven by IoT solutions) is increasing. Companies are looking at setting
up newer workplaces driven by technology for easier management and providing
enhanced employee experiences – whether it is hot desking or tailored provisioning of
experiences as employees become more mobile across their facilities
o Automation & Remote Management of Edge Infrastructure – COVID has amplified the
need to keep operations running, in spite of limited labor and constraints like people not
being able to spend time in-person troubleshooting their operational infrastructure. Plato
famously wrote: “our need will be the real creator” & could not be more true in these
times. Adoption of automation, workflows & remote management capabilities has
become a priority for companies who want to rely less on manual ways of doing things.
We see an increase in budget allocations within companies towards such initiatives, as
part of their risk mitigation strategies & business continuity procedures.
• ~2 or >2+ Years Horizon
On a long term basis, what will drive continued growth and adoption are mainly:
o 5G & NB-IoT – Connectivity becoming ubiquitous & cheaper to embrace. Enables billions
of devices to be connected and provide intelligence around them. The rise of PCN (Private
Cellular Network) deployments is leading to a data led but locally managed scenarios.
o MEC (Mobile Edge Compute) – Whether it is driven by Telcos or Hyperscalers or OEMs,
the need for high-performing, small-footprint Edge compute form factors are coming into
the market. Driven primarily through availability of bigger bandwidths (like 5G) and also
the realization that not all data & transactions has to go to the cloud because of costs &
o Legislation – In 2021 (for the first time), the Executive Order on Improving the Nation’s
Cybersecurity” covered the importance of securing both IT and OT infrastructure (which
includes IoT). Also there was emphasis on adoption of Zero Trust architecture in the IOT
world, especially from a cybersecurity perspective. Not only government agencies and
policy makers are looking at the IoT industry, but other industry bodies (ISO, SOC2) are
looking at whether they should embrace IoT infrastructure, policies, etc as part of their
o Digital Twins – Representation of real world in a digital world…models aimed at defining
and representing the physical world of machinery, sensors, etc. Getting rapid adoption
within Manufacturing, Utilities, etc. Virtual models that can be used to learn from physical
objects (machinery, sensors, etc), run simulations, study performance issues and generate
possible improvements, all with the goal of generating valuable insights — which can then
be applied back to the original physical object.
o AR/VR – Data from IoT-enabled devices is collected, converted into information and made
visible in real time through the likes of augmented (AR) and virtual reality (VR).
Applications include AR/VR for field force support (repairs, troubleshooting), design
simulations, spatial analysis. It is gaining rapid adoption not only in enterprises
(Manufacturing, Utilities, Oil & Gas, etc) but also among consumer use cases (Gaming –
Pokemon Go is a classic example of a very successful AR video game, driven by IoT