SandLogic, a prominent player in the Computer Vision and Edge AI space (Neural Net localisation), has raised $4 million in funding in its pre-Series A round from USA’s Texas-based HNIs and serial investors Sanjay Singhania and Sai Kumar. Their homegrown SaaS platform helps ML developers optimise, convert, and port their Neural Net/Deep Learning models onto targeted hardware.
This round follows the $360,000 seed round (backed by US-based Google and AT&T executives) at the end of 2020, bringing the startups' total funding to about $4.36 million.
“We are aiming to hyper-scale the company growth by doubling its strength and increase the revenue by 3x. Majority of this investment will help us in commercialising our products (EdgeMatrix and Vision SDK) at scale, hiring the right talent in USA and India, and in new customer acquisition,” says Kamalakar Devaki, Founder and CEO, SandLogic.
The emergence of Edge AI has been instrumental in allowing companies to have their data analysed and processed at the edge (near the data source) itself.
“Strides in the efficacy of AI, adoption of IoT devices, need for endpoint computing, and real-time inference of Deep Learning models are some factors resulting in the supersonic growth of Edge AI adoption,” say the investors.
AI that powers enterprises
Founded in 2018 by Kamalakar Devaki, Jesudas Fernandes, Radhika Kanigiri, and Ravi Kumar Rayana, Texas and Bengaluru-based SandLogic aims to enable industries to adopt AI economically and faster using their Edge AI platform and Vision SDK (ready to use Deep learning models APIs).
With its homegrown India’s first enterprise-ready low code/no code platform (EdgeMatrix.io), the company is accelerating the development and porting of Deep Learning models on Edge devices and managing the entire Edge AI lifecycle.
EdgeMatrix.io is the solution for brands aiming to federate AI or complex Deep Learning models onto any low-cost edge devices or looking at porting your existing models onto any target hardware (and yet aiming to retain the accuracy).
Sandlogic.ai strives to provide a seamless, easy, and fast end-to-end Edge AI accelerator platform so that brands can deploy Neural Nets onto countless devices.
ML developers use the platform to:
1. Port their existing AI models to any existing H/W - RISCV, ARM, x86, etc.
2. Leverage the toolchain to create new AI SoC coupled with low cost existing computes
“SandLogic has already proven themselves by adding AI (Deep Learning abilities) on India's first homegrown microprocessor Shakti Vajra (by IIT Madras) and demonstrated it in Digital India’s Azadi Ka Digital Mahotsav,” says Kamalakar Devaki, Founder and CEO, SandLogic.
The company is actively working on expanding its team, distributed across two countries, and is hiring across leadership, engineering, and marketing teams. The startup is also taking a big leap in partnering with various SOM / semiconductor companies like Xilinx, NVidia, Renesas, eInfochips, and more.
Growth and investments
SandLogic founders say that they are thankful to all the investors for believing in the team’s vision and products. They also added that they believe this association will help the company grow as a strong global brand for AI.
“When SandLogic reached out to us, we were very clear since day 1 that this company has the right fire, hunger, and grit to become a leading AI brand on a global scale. SandLogic products add a layer of intelligent piping across the business processes that connect the right information to automate and get the optimal value,” say investors Sanjay and Sai.
SandLogic derives its name from sand and logic, the two key bases of silicon and intelligence. Since its inception, the organisation has been on a mission to enable enterprises in their digital transformation and automation journey.
From Edge AI to building complex AI models, SandLogic’s products and frameworks have been tackling several challenges faced by businesses and developers alike.
To know more you can check out their website: www.sandlogic.com, contact them at sales@sandlogic.com, and follow them on LinkedIn.