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One-year-old enterprise AI solutions provider Ema already has an impressive list of backers; it has raised $25 million from investors such as Accel, Section 32, and Prosus Ventures. 

At a time when every other company claims to be the “next big thing” in the generative artificial intelligence (Gen AI) space, why are investors betting on Ema?

From building chatbots, code generation and design processes, enterprises are increasingly exploring Gen AI for various use cases. San Francisco and Bengaluru based Ema, short for Enterprise Machine Assistant, says it offers solutions to streamline these tasks, reduce costs, and accelerate development processes.

Earlier this month, the startup emerged from stealth to launch its Universal AI Employee, a solution that Ema says, will change how enterprises work. 

Ema was launched last March by Surojit Chatterjee, Souvik Sen, Swati Trehan.

“Our goal is to automate mundane tasks for businesses. What’s unique about Ema is that we have been a universal AI employee who can morph or take on any role in the enterprise,” Chatterjee, Founder and CEO of Ema AI tells YourStory.

The market opportunity is substantial. As per a report by Bloomberg Intelligence, the projected market size for generative AI in enterprises globally is set to reach $1.3 trillion by 2032.

The co-founders’ background also provides wings to the startup’s ambitions. Chatterjee previously guided Coinbase through a successful 2021 IPO as its Chief Product Officer and scaled Google Mobile Ads and Google Shopping as the VP and Head of Product. An MBA from MIT, Chatterjee holds 40 US patents on machine learning, ad-tech and enterprise software. 

Sen previously served as Okta’s VP of Engineering, along with being the Engineering Lead in Data and Machine Learning, Privacy and Safety at Google. A Harvard Business School MBA graduate, Trehan has led R&D Operations teams at Shopify after serving at McKinsey & Co and Google.

While the startup has many things going for it, the increasingly crowded market poses a significant hurdle. The number of Gen AI startups for enterprises stands at 67,200 in 2024, with an estimated increase from approximately 50,000 companies in December 2023, reports The Information. 

Ema’s immediate competitors are Quantive and Workboard, with the latter raising  $75 million in growth funding led by SoftBankVision Fund 2.      

As per a Deloitte report titled The State of Generative AI in the Enterprise, governance failures, leadership driving AI integration, LLMs adoption, customisation hurdles, data privacy concerns, talent shortages, ROI validation are some of the key challenges faced in the larger enterprise Gen AI space.

Mimicking human capabilities

Currently, enterprises have dozens of major Large Language Models (LLMs) and hundreds of LLMs to choose from, making it harder for them to select a specific LLM for a particular use case. 

Ema says it makes this process simpler. The platform integrates with hundreds of enterprise apps, saving time that requires onboarding new technology, according to the co-founder.

Its Universal AI Employee is designed to imitate human employees. It can engage in conversations, comprehend context, take continuous human feedback, and reason. This allows users to make better decisions, also allowing the AI to collaborate with humans on complex projects.  

“For any task at hand, it is essential to create a plan. As humans, when faced with a task like cooking, we naturally seek out a recipe. This involves researching on platforms like YouTube, studying the recipe, and analysing the steps involved to successfully execute the task,” Chatterjee explains. 

According to the co-founder, Ema also helps with executing tasks. 

For example, Ema’s Customer Support Persona can automatically resolve tickets within the company’s existing ticketing system. In doing so, Ema can not only respond to the customer’s inquiry but can also take appropriate actions, such as updating a shipping address for an order.

“The AI employee takes any complex task in hand and breaks it down into simpler tasks and executes them. It will figure out each of the sub tasks in that workflow, and how to execute them optimally. And to do that, some of the sub tasks may be just deterministic algorithms,” he adds.  

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What does Ema do? 

The startup’s AI employees, also called Personas, are powered through Generative Workflow Engine (GWE). The technology can generate new workflows with a conversational description of the problem by breaking the problem down into subtasks. 

It decides and orchestrates how to perform each subtask, taking actions over multiple enterprise applications and operating on a wide variety of data sources. Ema’s AI Employees have long-term memory that allows them to take feedback from human users and incorporate it to continuously improve their performance.

The startup says it ensures data security by safeguarding and segregating private data to prevent any mingling between different customers’ data. 

“Ema will automatically de-identify sensitive fields such as social security numbers, before transmitting data to any public platform, thereby mitigating the risk of any data leakage,” Chatterjee added.

Backed by Silicon Valley

The AI startup has garnered investment from several top Silicon Valley names, including Sheryl Sandberg, former COO, Meta ; Dustin Moskovitz, Co-founder, Facebookand Asana; Jerry Yang, Co-founder of Yahoo; Micky Malka, Founder of Ribbit Capital, and Sridhar Ramaswamy, CEO of Snowflake.

Envoy Global, TrueLayer and Moneyview are among the enterprises that have onboarded Ema’s personas instead of building new Gen AI applications. The startup onboarded these clients while still on stealth mode. 

TrueLayer, a European financial payment network, leverages Ema for technical support, enabling their clients to utilise their services for connecting with banks to facilitate payment processing. 

“The addressable market potential is incredibly large. We are fortunate to have strong industry support from top investors and leading enterprise software clients,” Chatterjee said.