Within the midst of a wave of tech industry layoffs, it’s heartening to see some startups succeeding despite the dour market outlook.
Kore.ai, an organization 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 corporate’s total raised to ~$223 million, the brand new money will probably be put toward product development and scaling up Kore.ai’s workforce, co-founder and CEO Raj Koneru told me in an interview.
Koneru began Kore.ai in 2014 after launching Kony, a mobile app development startup, and a number of other other small corporations 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 rework user experiences.
“With the introduction of GenAI and LLMs, the tech landscape turned out to be very chaotic and unsure as a result of rapid advancements,” Koneru said via email. “There have been more questions than answers … but I saw conversational AI and LLMs as a chance to innovate.”
GenAI being a more moderen discipline, Kore.ai wasn’t developing GenAI products in 2014 per se. But Koneru says that the corporate was laying the foundations for GenAI products to come back — 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 assist corporations 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 provide corporations in industries equivalent to banking, healthcare and retail the flexibility 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 every kind of customer experience and worker experience use cases,” Koneru said. “As well as, Kore.ai’s array of industry and horizontal solutions address the needs of specific industries and enterprise functions.”
But aren’t there numerous vendors constructing GenAI- and LLM-powered solutions for search, question-answering and the opposite styles of applications Kore.ai advertises supporting? Indeed, there are.
See Acree, which hosts a platform for constructing corporate GenAI apps, and Giga ML, which offers tools to assist corporations deploy LLMs offline. Reka and Contextual AI each recently emerged from stealth to assist create custom AI models for organizations, while Fixie is crafting tools to make it easier for corporations to code on top of LLMs.
What Kore.ai does in a different way, Koneru asserts, is offer great flexibility where it concerns where corporations can deploy their AI apps — within the cloud, locally or in virtual machines — and the degree to which they’ll fine-tune these apps. For certain applications (e.g. text summarization, finding and generating answers, topic discovery and sentiment evaluation), 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, in addition to more cost effective.
There’s a privacy argument to be made, too, for smaller, offline models.
A 2023 Predibase survey found that greater than 75% of enterprises don’t plan on using industrial, 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 companies said that they’re concerned about GenAI’s privacy and security risks.
Making a GenAI or conversational AI workflow using Kore.ai’s web tooling.
“Over the past 18 months, we’ve observed that fine-tuned models are very effective in comparison with pre-trained models for specific enterprise use cases,” Koneru said. “In comparison with a big pre-trained model, it takes lower than 2% of the enterprise data to coach and create a fine-tuned model that corporations can deploy safely for enterprise use cases. We’ve successfully built smaller enterprise LLMs that provide higher efficiency, higher accuracy, the flexibility to regulate responses and — most significantly — reduce latency and value.”
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 latest and diverse domains.
“Kore.ai sits above the infrastructure and fragmentation of all of the LLM layers with a platform-driven approach, offering freedom of selection 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 one platform to let customers deploy models in a spread 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 a powerful foothold within the competitive AI field. The corporate’s customer base eclipsed 400 brands (including PNC, AT&T, Cigna, Coca-Cola, Airbus and Roche) last yr, and its annual recurring revenue now stands north of $100 million — because of income from licensing and usage fees along with consulting services.
It probably helps that funding for GenAI startups of all stripes stays strong. In keeping with 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 in comparison with 2021.
The query is whether or not the expansion is sustainable, provided that GenAI isn’t a house run within the enterprise — not less than not yet. Koneru argues that it’s, 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 equivalent to customer support, marketing and sales.
“We haven’t observed any slowdown available in the market,” Koneru said. “Probably the most pressing challenge [we’re facing] is to operate and innovate in a market that’s not only seen rapid growth but additionally disruption driven by advancements in technology, changing user expectations and a broader integration of newer AI capabilities which are evolving every day. Enterprise players have to make the most of the advantages of technology while avoiding security, privacy and compliance pitfalls.”
Added FTV Capital’s Kapil Venkatachalam in an announcement: “While the advanced AI market has experienced rapid growth lately, many enterprises are grappling with how one can 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 make the most of the growing demand from global brands searching for revolutionary AI solutions to reinforce business interactions and drive value.”
