Regular updates on the latest VC-backed AI startups. Follow along to stay informed!
Predibase, an end-to-end machine learning platform, raised $12.2M in Series A expansion funding (in addition to its $16.3M Series A from last year). Felicis Ventures led the round.
Problem to be Solved
Every enterprise wants to gain a competitive edge by embedding ML into their internal and customer-facing applications, but today’s ML tools are too complex for engineering teams, and data science resources are stretched too thin, leaving the developers working on these projects holding the bag.
How They Use AI
Predibase builds MLOps tools to make it simple for novices and experts alike to build ML applications and get them into production with just a few lines of code. Their product does not really use AI. Instead, it helps developers include AI in their products with as little overhead as possible. After skimming over their codebase, it looks like a very intuitive product.
Business Model
After a two-week free trial, customers pay a subscription fee for access to the low-code ML platform. Current customers include Paradigm and Koble.ai, and users have trained over 250 models on the platform since it came out of stealth last year.
Sana, an AI-powered enterprise learning and knowledge platform, raised $28M in Series B expansion funding (in addition to the $34M Series B from last year). NEA led the deal, with participation from Workday Ventures.
Problem to be Solved
Institutional knowledge today is scattered across multiple tools, trapped in people's minds, and lost in verbal conversations. Sana wants to use AI to solve this problem at scale by blending the best of enterprise search, a learning management system, meeting tools, and a knowledge management system into one single platform.
How They Use AI
Sana uses AI to “generate questions, explanations, images, and even entire courses”. The product also includes an AI search bar to answer questions based on the company’s internal knowledge base. At a high level, their course generation feels very similar to MindSmith, a company we covered last month. The AI search bar is also in high competition with multiple plug-and-play solutions emerging from startups (e.g. Mendable) and enterprises alike (e.g. HubSpot). Sana’s competitive advantage is not so much its technology as it is its niche of employee onboarding.
Business Model
Classic SaaS. Customers include Klarna, Lyko, and other large European enterprises, but most of these bought the L&D SaaS before Sana added AI features.
8Flow.ai, a self-learning workflow automation engine, raised $6.6M in Seed Funding. 8Flow‘s seed round was led by Caffeinated Capital, with BoxGroup, Liquid2, HNVR, and Trilogy also joining.
Problem to be Solved
Working in customer support often means navigating disjointed tools to find data and solve issues. However, many of these actions are routine and repeatable, making them ideal candidates for automation, which is exactly what 8Flow.ai aims to do.
How They Use AI
Hard to say. While it’s unclear, it’s unlikely 8Flow is using AI to detect common customer service “flows”. In theory that could be done by storing an agent’s sequence of actions and searching for patterns. The auto-complete features might be leveraging a language model to extract information from the customer service chat. Until the company releases more information, we’re left speculating.
Business Model
TBD. The company was in stealth mode until this funding announcement, and the website currently only features a link to “request early access”, but this will presumably be sold on a SaaS model.