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$34 Million For Its AI-Based Workplace Learning And knowledge Management Platform.

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$34 Million For Its AI-Based Workplace Learning And knowledge Management Platform.

Thanks to: Yuichiro Chino/Getty Images (opens in a new window) Artificial intelligence is affecting every facet of our interaction with information today—and much more. Today, a startup that is developing a business around a specific application of that—how to apply AI to workplace knowledge management—is announcing funding as its strategy gains some respectable traction. After seeing ARR grow sevenfold in the past year, Sana Labs, which provides an AI-based platform to assist individuals in managing information at work and then using that data as a resource for e-learning within the organization, has closed a round of $34 million.

The round for Stockholm-based Sana is led by Menlo Ventures, a US venture capital firm. EQT Ventures and a whopping 25 angel investors and founder/operator individuals are also participating. Sana is valued at $180 million post-money in this Series B.

There are a lot of enterprise search, enterprise learning, and knowledge management products on the market today; however, Sana believes it has found a platform that unites all three: a platform that combines enterprise search with e-learning and knowledge management.

The core of Sana is a stage and artificial intelligence motor that interfaces with all of the different applications that an association involves in the working environment — Salesforce, email, Idea, Github, Slack, Trello, Asana, and whatever else you could need to catch, source or store data and speak with others.

The Sana platform (AI magic) automatically ingests and organizes all of the data in these apps. It also keeps track of the data as it changes or grows in those apps. After that, users who wish to access information go to Sana and make a request for it using standard “human” language, just like they would in a search engine. On the other hand, the data are used to build e-learning modules for onboarding, training, or professional development. These modules can be made by Sana employees or by Sana itself.

Sana didn’t start with this idea; instead, it started by building just the back-end machine learning engine to organize data. However, Sana’s CEO and founder, Joel Hellermark, stated that the startup’s front end, which allows users to easily query the information and use it to create training and learning materials, was requested early on, so they also built that component. The learning can take the form of quizzes, polls, interactive sessions, and more. When interactive Q&A is created around webinars, it’s like a very resourceful, waste-not-want-not stew, and the results are added to the knowledge base for later use.

Hellermark stated, “The platform sees very different engagement metrics because of the mix of knowledge management, search, and e-learning.” Sana is utilized continuously, which sets it apart from typical e-learning platforms,” he stated. We’re seeing week by week and everyday dynamic utilization” from among the huge number of representatives from across the 100 or so organizations that are as of now utilizing Sana, he added.

Hellermark stated that although Sana develops and customizes the technology itself, OpenAI, which has a “deep partnership” with Sana, provides the models.

He stated, “We’ve been using their models continuously since day one, before launch.” This includes GPT, which has been the topic of conversation on Twitter among tech and media professionals via ChatGPT. In the long run, the scalable potential of AI is demonstrated by Sana’s strategy.

Hellermark added, “We believe there will be underlying models from the likes of OpenAI with the possibility of fine-tuning them for specific domains.” In addition to this, the user experience is our primary focus.

Hellermark says that he has been obsessive about AI’s ability to make a name for itself in the industry and the significance of education. However, there are many different kinds of education—professional development, adult education, content for younger people, and further education are just a few examples.

According to him, Sana decided for two reasons to concentrate on the fourth of those. The first is that it is practical. There is nothing like it on the market right now, but given the abundance of useful information in an organization’s braintrust that works on an inverse variation, it is definitely something that organizations could use. It becomes more difficult to access it the more it accumulates.

The scalability factor is the second reason for the enterprise focus: While it is evident that traditional education could benefit from tools for ingesting a large amount of dispersed, fragmented information, making it easy to access, and using it as the basis for learning modules that are tailored to each student, the fragmentation of information across age groups, school districts, and countries, let alone their own distinct curriculums, makes it a more difficult target. This may be the case even more so right now, given the emphasis that startups and their backers are placing on projects that have solid unit economics

He stated, “My greatest passion is the education sector because if you solve learning, you solve everything.” But from the beginning, we wanted to be a big business. It’s hard to grow that big in K-12 because you have to change for each country. Having a venture approach helps us scale and helps specialists to designers and item supervisors and agents and everybody. We are able to serve them all in more than 20 nations.

Importantly, this does not mean that this will not be a target in the future or that the traditional education sector will not be a receptive customer for Sana or another startup’s technology in the future.

How Sana deals with the quality of the information it sources is yet another important aspect to take into consideration. Can it make a decision? How does it decide? if the data it sources is accurate; if multiple “answers” are inconsistent with one another, what does it do?

Hellermark stated in response to the question, “That is what knowledge management is.” Models that only search can be used, but that doesn’t take into account the need to verify information and create journeys. He stated that the system has a “structure for verification,” which allows individuals to restrict the input from sources and other sources.

be used by Sana, and customers can choose which information is verified and accurate, whether unverified information can be accessed by users, and how information is ranked.To be honest, it is not a completely satisfactory response, especially considering that accuracy is one of the most persistent AI issues: What should you do if it isn’t quite right, is completely wrong, or uses bad data?However, unlike the rest of the AI rocket ship, this has not hindered Sana’s development yet.JP Sanday, the Menlo partner who led this investment, stated, “Over the past six years, I’ve looked at almost every other learning management system SaaS, and the best part about Sana is that they are building a true knowledge management solution from the ground up, considering how knowledge is captured in today’s knowledge economy.” Companies are now more dispersed, have to do more with less, and cannot keep up with the rate of innovation. As a result, they need to provide opportunities for all of their employees. The only platform I’ve ever seen that can realize this vision is Sana.He added that a particular “organizational knowledge graph” that is more democratized than what you typically get in organizations is created when people both tap into the database and build content around it.He stated, “When I show prospects the product and they see the content creation experience as well as the AI capabilities that help both authors and learners, they immediately know they are looking at something completely different — they see how much more extensible it is and how much more engagement they get from users.” “They see how much more extensible it is and how much more engagement they get from users.”

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