Artificial intelligence today touches every aspect of how we deal with information (and much more). Today, a startup that’s building a business around a specific application of it — how to apply AI to knowledge management in the workplace — is announcing funding because it’s finding decent traction for its approach. Sana Labs — which provides an AI-based platform to help people manage information at work and then use that data as a resource for e-learning within the organization — has closed a $34 million round, after the ARR grew sevenfold last year.
Menlo Ventures, the US VC firm, is leading the round for Stockholm-based company Sana, with EQT Ventures and a whopping 25 angels and founder/operators also participating. This is a Series B, valuing Sana at $180 million when cashed.
There are many knowledge management, enterprise learning, and enterprise search products on the market today, but what Sana believes has encountered a unique platform that combines all three to work together: Knowledge Management-meets-Enterprise-Search-meets-E-Learning Platform.
At the core of Sana is a platform and AI engine that connects to all the different apps a company uses in the workplace – Salesforce, Email, Notion, Github, Slack, Trello, Asana, and whatever else you need to track , obtain or store information and communicate with others.
All data from these apps is automatically collected and organized by the Sana platform (AI Magic) and maintained as the information in these apps changes or expands. Then users who want to access information go to Sana and request it in normal “human” language, like you might do in a search engine. But alongside this, the data is used as the basis for e-learning modules for onboarding, training or professional development – modules created/thought out either by people in the organization or by Sana itself.
This wasn’t the original concept for Sana, which started by building just the back-end machine learning engine to organize information. But Joel Hellermark, CEO and founder of Sana, said the startup got requests early on for the front end – the part for people to easily query the information and use it to create training and learning materials – so they have that part also built. Learning can come in the form of quizzes and surveys, interactive sessions and more, and when interactive questions and answers are generated around webinars, like some kind of very imaginative stew where you don’t want to waste anything, the results from all of these are obtained too fed into the knowledge base for future reference.
The mix of knowledge management with search and e-learning means the platform sees very different engagement metrics, Hellermark said. “Sana is used continuously, which is very different from a typical e-learning platform,” he said. “We’re seeing weekly and daily active use” among the tens of thousands of employees from the 100-odd companies already using Sana, he added.
The technology itself is developed and customized by Sana, but the models, Hellermark says, come from OpenAI, which Hellermark says has a “deep partnership” with Sana.
“We’ve used their models continuously from day one, even before they were launched,” he said. This includes GPT, which – via ChatGPT – has been the talk of the town among tech and media people on chatty platforms like Twitter. Sana’s approach speaks to the scalable potential of AI over the longer term.
“We believe there will be underlying models like OpenAI, with the ability to optimize them for specific domains,” Hellermark added. “For us, the focus is also on the user experience.”
Hellermark describes himself as a long-time obsessed not only with the importance of education, but also with the power of AI to make its mark in space. But education comes in many forms – content aimed at younger people, continuing education, adult education and professional development are just some of the pieces of the pie.
He said Sana chose to focus on the fourth for two reasons. The first is due to practicality – there’s not really anything like it on the market today, but it’s definitely something organizations could use, given the glut of useful information contained in an organization’s braintrust, that’s on a reverse twist works: the more of it is accumulated, the more difficult it becomes to tap it.
The second reason for the corporate focus lies in the scalability factor: while education in the more traditional sense could clearly use tools to take in lots of disparate, fragmented information and make it easily accessible and form the basis for learning modules tailored to the individual, the fragmentation across age groups and school districts, not to mention countries and their own specific curricula, makes it a more complicated goal — perhaps even more so, given the emphasis we’re seeing from startups and their supporters to focus on projects with sound single economics, identifiable ones (and active) customer bases and technology already working for those purposes.
“Education is my biggest passion because when you solve learning, you solve everything,” he said. “But from day one we wanted to be a big company and it’s difficult to scale that in K-12 because you have to adapt to different countries. An enterprise-centric approach helps us scale, helping doctors, engineers, product managers, sales reps and everyone. We can serve them all in over 20 countries.”
Importantly, that doesn’t mean that this won’t be a goal in the longer term, or that the traditional education sector wouldn’t or couldn’t be a receptive customer for such technologies – from Sana or any other startup – in the long term.
Another important detail to consider is how Sana handles the quality of the information it sources. How does it decide – can it decide? — whether the data it originates is correct, and what does it do if there are several “answers” that do not match each other?
“That’s knowledge management,” Hellermark answered the question. “You can have models based solely on search, but that doesn’t account for the need to verify knowledge and create journeys.” He said there is a “structure for verification” built into the system that involves people limit what sources and other submissions can be used by Sana, allowing customers to choose what information is verified and accurate, and whether users can access and categorize information that is unconfirmed.
To be honest, this isn’t a fully satisfactory answer, especially since accuracy is one of the most persistent problems related to AI: what do you do when it’s not entirely right, entirely wrong, or just using bad data?
However, as with the rest of the rocketship being AI, this wasn’t an issue hindering Sana’s growth for now.
“In the last 6+ years I’ve looked at almost every other SaaS learning management system and the best thing 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” said JP Sanday, the Menlo partner who led this investment. “Companies are now more distributed, challenged to do more with less, struggling to keep up with the pace of innovation and needing to empower all of their employees. Sana is the only platform I’ve seen that can fulfill that vision.”
He added that the approach of people both accessing the database and creating content around it creates a specific “organizational knowledge graph” that’s more democratized than what you typically get in organizations.
“When I show prospects the product and they see the content creation experience and 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’re getting from users,” he said.