Simplismart secures USD $7m to enhance AI for enterprises

Simplismart, a startup focused on advancing AI adoption in enterprise settings, has secured USD $7m in a series A funding round led by Accel.

Simplismart has announced the development of the fastest inference engine while receiving substantial financial backing to bolster its AI deployment capabilities. The funding round, which also involved contributions from Shastra VC, Titan Capital, and notable angel investor Akshay Kothari, Co-Founder of Notion, will support research and development and the growth of its MLOps orchestration platform tailored for enterprises.

Founded in 2022 by former Oracle and Google engineers Amritanshu Jain and Devansh Ghatak, Simplismart has in a brief span of two years with less than USD $1m in initial funding, delivered significant performance benchmarks. The company's inference engine enables organisations to efficiently run machine learning models while optimising both speed and cost-effectiveness.

Co-Founder and CEO Amritanshu Jain highlighted the challenges faced by enterprises in embracing generative AI technologies. "Building generative AI applications is a core need for enterprises today. However, the adoption of generative AI is far behind the rate of new developments. It's because enterprises struggle with four bottlenecks: lack of standardized workflows, high costs leading to poor ROI, data privacy, and the need to control and customise the system to avoid downtime and limits from other services," he explained.

Simplismart's solution provides a standardised language akin to Terraform, which allows software engineers to streamline deployment, fine-tuning, and monitoring of generative AI models. By addressing these concerns, enterprises can focus on core product improvements rather than building intricate infrastructures.

Jain elaborated on the necessity of comprehensive orchestration workflows as enterprises handle larger AI models and workloads. He remarked, "Until now, enterprises could leverage off-the-shelf capabilities to orchestrate their MLOps workloads since the quantum of workloads, be it the size of data, model or compute required, was small. As the models get larger and the workload increases, it will be imperative to have command over the orchestration workflows. Every new technology goes through the same cycle: exactly what Terraform did for cloud, Android studio for mobile, and Databricks/Snowflake did for data."

Anand Daniel, Partner at Accel, echoed this sentiment and emphasised the rising demand among developers for customisable and security-focused AI model deployment. "As GenAI undergoes its Cambrian explosion moment, developers are starting to realise that customizing & deploying open-source models on their infrastructure carries significant merit; it unlocks control over performance, costs, customizability over proprietary data, flexibility in the backend stack, and high levels of privacy/security," Daniel noted. He further praised Simplismart for identifying the market need early and making remarkable progress with limited resources.

Simplismart seeks to empower enterprises by offering modular solutions in their inference engine and deployment strategies, enabling them to optimise performance and cost balance according to specific operational needs.