Kore.ai, a startup building conversational AI for enterprises, raises $150M

In the midst of a wave of tech industry layoffs, it’s heartening to see some startups succeeding despite the dour market outlook.

Kore.ai, a company developing enterprise-focused conversational AI and GenAI products, today announced that it raised $150 million in a funding round led by FTV Capital, Nvidia, Vistara Growth, Sweetwater PE, NextEquity, Nicola and Beedie. Bringing the company’s total raised to ~$223 million, the new cash will be put toward product development and scaling up Kore.ai’s workforce, co-founder and CEO Raj Koneru told me in an interview.

Koneru started Kore.ai in 2014 after launching Kony, a mobile app development startup, and several other small companies including iTouchPoint (an outsourcing firm) and Intelligroup (a tech consultancy). He says he was inspired to found Kore.ai after seeing the potential of AI, particularly large language models (LLMs) along the lines of OpenAI’s ChatGPT, to transform user experiences.

“With the introduction of GenAI and LLMs, the tech landscape turned out to be very chaotic and uncertain due to rapid advancements,” Koneru said via email. “There were more questions than answers … but I saw conversational AI and LLMs as an opportunity to innovate.”

GenAI being a newer discipline, Kore.ai wasn’t developing GenAI products in 2014 per se. But Koneru says that the company was laying the foundations for GenAI products to come — investing heavily in text-generating and -analyzing models.

So how’s Kore.ai innovating? Well, as Koneru describes it, the startup provides a no-code platform to help companies power various “business interactions” via AI — essentially any customer-to-employee or employee-to-employee interaction over the phone or text (think support chats with an IT/HR service desk). Kore.ai offers workflows and tools designed to give companies in industries such as banking, healthcare and retail the ability to create custom conversational AI apps or deploy pre-built, “domain-trained” chatbots.

“Kore.ai’s platform encompasses intelligent virtual agent, contact center AI, agent AI and search and answer capabilities for all kinds of customer experience and employee experience use cases,” Koneru said. “In addition, Kore.ai’s array of industry and horizontal solutions address the needs of specific industries and enterprise functions.”

But aren’t there lots of vendors building GenAI- and LLM-powered solutions for search, question-answering and the other sorts of applications Kore.ai advertises supporting? Indeed, there are.

See Acree, which hosts a platform for building corporate GenAI apps, and Giga ML, which offers tools to help companies deploy LLMs offline. Reka and Contextual AI both recently emerged from stealth to help create custom AI models for organizations, while Fixie is crafting tools to make it easier for companies to code on top of LLMs.

What Kore.ai does differently, Koneru asserts, is offer great flexibility where it concerns where companies can deploy their AI apps — in the cloud, locally or in virtual machines — and the degree to which they can fine-tune these apps. For certain applications (e.g. text summarization, finding and generating answers, topic discovery and sentiment analysis), Koneru makes the case that fine-tuned models — Kore.ai’s speciality — are superior to the larger, more powerful models available from vendors like Anthropic and OpenAI, as well as more cost-effective.

There’s a privacy argument to be made, too, for smaller, offline models.

A 2023 Predibase survey found that more than 75% of enterprises don’t plan on using commercial, cloud-hosted LLMs in production over fears that the models will compromise sensitive info. In a separate poll from GenAI platform Portal26 and data research firm CensusWide, 85% of businesses said that they’re concerned about GenAI’s privacy and security risks.

“Over the past 18 months, we’ve observed that fine-tuned models are very effective compared to pre-trained models for specific enterprise use cases,” Koneru said. “Compared to a large pre-trained model, it takes less than 2% of the enterprise data to train and create a fine-tuned model that companies can deploy safely for enterprise use cases. We’ve successfully built smaller enterprise LLMs that provide higher efficiency, better accuracy, the ability to control responses and — most importantly — reduce latency and cost.”

Also unlike some rivals, Kore.ai offers ways for organizations to scale up their AI as needed, Koneru says, and expand their use of AI into new and diverse domains.

“Kore.ai sits above the infrastructure and fragmentation of all the LLM layers with a platform-driven approach, offering freedom of choice with built-in guardrails for effective AI implementation,” Koneru added.

Now, the extent to which these capabilities are truly differentiating is subject to debate. Vendors like Google Cloud, Azure and AWS offer robust scaling solutions for conversational AI and GenAI apps, and Kore.ai isn’t the only platform to let customers deploy models in a range of local and cloud compute environments.

But — whether on the strength of its platform, nearly-1,000-person-workforce, marketing campaign or all three — Orlando, Florida-based Kore.ai has established an impressive foothold in the competitive AI field. The company’s customer base eclipsed 400 brands (including PNC, AT&T, Cigna, Coca-Cola, Airbus and Roche) last year, and its annual recurring revenue now stands north of $100 million — thanks to income from licensing and usage fees in addition to consulting services.

It probably helps that funding for GenAI startups of all stripes remains strong. According to a recent survey from GlobalData, the London-based data analytics and consulting firm, GenAI startups raised a record $10 billion in 2023 — a 110% increase compared to 2021.

The question is whether the growth is sustainable, given that GenAI isn’t a home run in the enterprise — at least not yet. Koneru argues that it is, pointing to surveys like Gartner’s from last October, which found that 55% of organizations are already piloting or deploying GenAI tech into production for functions such as customer service, marketing and sales.

“We haven’t observed any slowdown in the market,” Koneru said. “The most pressing challenge [we’re facing] is to operate and innovate in a market that’s not just seen rapid growth but also disruption driven by advancements in technology, changing user expectations and a broader integration of newer AI capabilities that are evolving each day. Enterprise players need to take advantage of the benefits of technology while avoiding security, privacy and compliance pitfalls.”

Added FTV Capital’s Kapil Venkatachalam in a statement: “While the advanced AI market has experienced rapid growth in recent years, many enterprises are grappling with how to responsibly and effectively deploy AI across their organizations. We were impressed with Kore.ai’s open platform approach for leveraging AI models, scalability, vertical specific out-of-the-box applications and low-code no-code capabilities, making them well-positioned to take advantage of the growing demand from global brands looking for innovative AI solutions to enhance business interactions and drive value.”