Artificial intelligence is touching every aspect of how we engage with information (and much more) these days. Today, a startup building out a business based on one particular application of that — how to apply AI to knowledge management in the workplace — is announcing some funding as it finds some decent traction for its approach. Sana Labs — which provides an AI-based platform to help people manage information at work, and subsequently to use that data as a resource for e-learning within the organization — has closed a round of $34 million after seeing ARR grow seven-fold in the last year.
Menlo Ventures, the U.S. VC firm, is leading the round for Stockholm-based Sana, with EQT Ventures and a whopping 25 angels and founder/operator individuals also participating. This is a Series B that values Sana at $180 million post-money.
There are a lot of knowledge management, enterprise learning and enterprise search products on the market today, but what Sana believes it has struck on uniquely is a platform that combines all three to work together: a knowledge management-meets-enterprise-search-meets-e-learning platform.
The crux of Sana is a platform and AI engine that connects to all of the different apps that an organization uses in the workplace — Salesforce, e-mail, Notion, Github, Slack, Trello, Asana, and whatever else you might have to capture, source or store information and communicate with others.
All of the data across these apps is ingested and organized automatically by the Sana platform (AI magic), and maintained as the information inside those apps changes or expands. Then, users who want to access information go to Sana and request it in regular “human” language as you might do in a search engine. But alongside that, the data is used to as the basis of e-learning modules for onboarding, training or professional development — modules created/conceived of either by people in the organization, or by Sana itself.
This wasn’t the original concept for Sana, which started with building just the back-end machine learning engine to organize information. But Joel Hellermark, Sana’s CEO and founder, said that early on the startup was getting requests for the front end — the part for people to easily query the information and use it to build training and learning materials — so they build that part, too. The learning can come in the form of quizzes and polls, interactive sessions, and more, and when interactive Q&A is generated around webinars, like some kind of very resourceful, waste-not-want-not stew, the outcomes from all those also get fed into the knowledge base for future reference.
The mix of knowledge management with search and e-learning means that the platform sees very different engagement metrics, said Hellermark. “Sana is used continuously which is very different from a typical e-learning platform,” he said. “We’re seeing weekly and daily active usage” from among the tens of thousands of employees from across the 100 or so businesses that are already using Sana, he added.
The tech itself is built out and customized by Sana, but the models, Hellermark said, come from OpenAI, which has a “deep partnership” with Sana, in Hellermark’s words.
“We’ve been using their models from day one continuously, since before launch,” he said. That includes GPT, which — via ChatGPT — has been the talk of the town among tech and media folk on chatty platforms like Twitter. Sana’s approach speaks to the scalable potential for AI longer term.
“We believe there will be underlying models from the likes of OpenAI with the opportunity to fine-tune them for specific domains,” Hellermark added. “For us, the focus is the user experience on top of this.”
Hellermark describes himself as a longtime obsessive about not just the significance of education, but of the power of AI to make a mark in the space. But education comes in many forms — content aimed at younger people, further education, adult learning, and professional development being just a few of the slices of the pie.
He said that Sana chose to focus on the fourth of those for two reasons. The first is because of the practicality of it — there isn’t really anything else like it on the market today, but it’s definitely something organizations could use, given the oversupply of useful information contained within an organization’s braintrust that works on an inverse variation: the more of it that is amassed, the harder it gets to tap into it.
The second reason for the enterprise focus is because of the scalability factor: while education in the more traditional sense clearly could use tools for ingesting lots of disparate, fragmented information and making it easily accessible and the basis of learning modules personalized to the individual, the fragmentation across age groups and school districts, let alone countries and their own specific curriculums, makes it a more complicated target — perhaps even more right now, given the emphasis we’re seeing from startups, and their backers, to focus on projects with sound unit economics, identifiable (and active) customer bases, and tech that already works to those ends.
“The education sector is my biggest passion because if you solve learning you solve everything,” he said. “But from day one we wanted to be a large company and it’s hard to scale that in K-12 because you have to adapt to different countries. Having an enterprise approach helps us scale and helps doctors to engineers and product managers and sales reps and everyone. We’re able to serve all of them in over 20 countries.”
Importantly, that’s not to say that this won’t be a target longer term, or that the traditional sector of education wouldn’t or couldn’t be a receptive customer for technology like this — from Sana or another startup — in the longer term.
Another important detail to consider is how Sana handles the quality of the information that it sources. How does it decide — can it decide? — if data that it sources is correct, and what does it do if there are multiple “answers” that are not consistent with each other?
“That is what knowledge management is,” Hellermark said in response to the question. “You can have models that are just search, but that doesn’t take into account the need to verify knowledge and create journeys.” He said that a “structure for verification” is built into the system, which includes people being able to limit what sources and other input can be used by Sana, with customers able choose to designate what information is verified and accurate, and choose whether users can access information that is unverified, and to rank information.
It’s not a fully satisfactory answer, to be honest, especially since accuracy one of the most persistent issues around AI: what do you do if it’s not quite right, or outright wrong, or simply using bad data?
As with the rest of the rocket ship that is AI, however, this for now has not been an issue impeding Sana’s growth.
“Over the past 6+ years, I’ve looked at almost every single 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,” said JP Sanday, the Menlo partner who led this investment. “Companies are now more distributed, are being asked to do more with less and cannot keep up with the pace of innovation and need to enable all of their employees. Sana is the only platform I have ever seen that can fulfill this vision.”
He added that the approach of people both tapping into the database, and building content around it, creates a specific “organizational knowledge graph” that is more democratized than what you typically get in organizations.
“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,” he said.
Sana raises $34M for its AI-based knowledge management and learning platform for workplaces by Ingrid Lunden originally published on TechCrunch