French startup Mud has raised a $16 million Sequence A funding spherical led by Sequoia Capital. With Mud, corporations can create customized AI assistants and share them with their staff in order that they will work extra effectively.
However what’s fascinating with Mud is the variations with different corporations engaged on enterprise brokers or AI assistants typically. Not like a consumer-facing instrument like ChatGPT, Mud assistants are related to an organization’s knowledge and paperwork. For example, once you construct a brand new assistant in Mud, you may affiliate it with Notion pages, paperwork saved in Google Drive, Intercom conversations or Slack.
On the identical time, not like most AI startups engaged on enterprise brokers, Mud believes that corporations ought to have a number of AI assistants — not only one. Every assistant may very well be helpful to carry out a sure set of duties and clear up some frequent issues {that a} particular staff is going through.
In additional sensible phrases, help groups can use a Mud assistant that’s conscious of each the content material of the information base and previous help interactions. This fashion, new staff members within the help staff can ask a query to the @supportExpert assistant and get a related reply.
HR groups can create an AI assistant that may reply questions on company insurance policies — no want to look a convoluted Notion database. They will additionally create a distinct agent that may draft job descriptions primarily based on previous job descriptions. As soon as once more, this empowers the corporate at massive and frees up time for the HR staff.
For engineering and knowledge groups, the use instances are fairly simple. For instance, a Mud assistant can pay attention to the corporate’s database schemas. You’ll be able to ask @SQLbuddy in plain English to write down a SQL question in your buyer base.
One final instance: gross sales groups can generate draft emails primarily based on CRM knowledge and the overall context behind a possible shopper. And if you want to create your individual connectors or combine Mud assistants in one other instrument, the corporate presents an API.
As a substitute of reinventing the wheel, Mud focuses on constructing a product that works for everybody. A few years after the launch of ChatGPT, most individuals at the moment are aware of AI assistant (many are even utilizing it for work regardless that its towards firm insurance policies). They know learn how to begin a dialog, observe up with extra particulars and ask the AI assistant to reframe its reply.
Utilizing Mud isn’t that totally different as corporations are constructing conversational assistants with the platform. Workers can then go to Mud’s net interface or work together with assistants in Slack straight — this fashion, they are often @-mentioned in the midst of a dialog. Mud primarily needs to show generative AI into an inner communication instrument that everybody makes use of each day.
The startup now generates $1 million in annual recurring income with some late-stage tech corporations utilizing it intensively, corresponding to Watershed, Alan, Qonto, Pennylane and PayFit.
Business banking startup Qonto estimates that 75% of its staff of 1,600 are utilizing Mud assistants on a month-to-month foundation. At Alan, a French medical insurance unicorn, 80% of the corporate makes use of AI assistants on a weekly foundation. Accounting tech unicorn Pennylane has created 86 customized assistants with Mud.
Along with Sequoia Capital, a number of the startup’s current buyers are investing as soon as once more, corresponding to XYZ, GG1, Join Ventures, Seedcamp and Motier Ventures.
Having a customer-focused method additionally implies that Mud isn’t creating its personal basis mannequin. While you construct an assistant, you may choose the massive language mannequin that you just need to use for that assistant. Mud has integrations with OpenAI (GPT), Anthropic (Claude), Mistral and Google for its Gemini fashions.
There are fairly just a few startups engaged on enterprise platforms for constructing AI brokers. Some names that come to thoughts are Brevian, Tektonic AI, Ema, Kore.ai and Glean. Even Atlassian, the enterprise software program big behind Jira and Confluence, has launched its AI teammate Rovo. Let’s see if Mud has discovered the appropriate go-to-market methodology with its straightforward onboarding technique.
