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Make no mistake about it: There is a lot of hype and a lot of money in play in the generative AI land grab.
Today, San Francisco-based startup Typeface announced it has raised $100 million in new funding to help expand its go-to-market efforts as the company builds out generative AI content services for enterprises. The triple-digit fund raise is particularly noteworthy as the startup only exited stealth in February, alongside $65 million in funding.
Earlier this month Typeface expanded its customized generative AI approach with a Google Cloud partnership. The company has also added partnerships with Microsoft and Salesforce in recent weeks, further expanding its reach.
Former Adobe CTO Abhay Parasnis leads the startup, which aims to empower prominent brands across diverse industries with the capabilities of generative AI. Typeface helps enterprises create content at scale using AI-generated text and images, with machine learning (ML) training that has been customized on an organization’s content. Recognizing the limitations of generalized large language models (LLMs) in meeting specific brands’ requirements, the company seeks to bridge the gap.
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“From Typeface’s perspective, the funding news underscores the broader trend of generative AI coming into focus for enterprise customers,” Parasnis, founder and CEO of Typeface, told VentureBeat. “Businesses are starting to really look at this [generative AI], not just as a cool technology with some demos, but rather are thinking about how it is going to actually materially change the businesses and transform workflows.”
Generative AI for the enterprise is all about workflow
While it’s still early days for gen AI, Parasnis said Typeface is already seeing significant growth in customers signing commercial contracts and in revenue. The company plans to use its new funding to accelerate product innovation around multi-modal generative pipelines and reimagining enterprise workflows in areas like marketing, HR and customer support.
“I think generative AI innovation is going to switch from platform innovation to workflow innovation,” Parasnis said.
As such, instead of organizations thinking about generative AI as a generic tool to generate content, the focus for Typeface is on helping enterprises with specific workflows optimize their business processes. Parasnis said that one of Typeface’s customers, for example, is using the technology to completely reimagine how all its employee communication happens. That includes workflows for generating LinkedIn job postings, employee communications and even payroll reports.
“That’s not what you would have thought six months ago about what generative AI could transform, but it is going to transform many enterprise workflows,” he said.
Understanding the gen AI maturity model
While there is no shortage of excitement around generative AI, Parasnis emphasized that not all enterprises are jumping on the bandwagon.
Parasnis is no stranger to the world of enterprise IT and how technology is adopted. He noted that even with the transition to cloud computing, which has been ongoing for a decade, not all enterprise workloads have moved to the cloud. In fact, many workloads continue to remain on-premises. He expects the transition to generative AI to follow a similar pattern, with different stages of adoption for different industries.
To help enterprises understand how generative AI can be adopted, Typeface has developed its own gen AI maturity model. The idea behind the model is to take a consultative approach that helps enterprise IT leaders understand AI and, specifically, how generative AI can change workflows.
“If you produce a certain amount of content today, using generative AI solutions like Typeface the enterprise can get significantly more content produced while still preserving brand voice and personalization,” Parasnis said. Describing what the company calls the “10x content factory,” he explained that “we define some very specific metrics for customers around investing in generative AI and how they measure it through the lens of more content produced that’s still on brand.”
Parasnis commented that for enterprises, adoption of generative AI is not just about technology. Rather he emphasized that new technology adoption is about process, culture and organizational change that have to be combined with the technology.
“Sometimes sitting in Silicon Valley, we have a tendency to think these transitions are going to happen much faster than they actually do,” he said.
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