AI chatbots are getting better at answering questions, summarizing documents and solving mathematical equations, but they still behave like helpful assistants for one user at a time. They’re not designed to handle the messy work of real collaboration: coordinating people with competing priorities, tracking long-term decisions, and keeping teams aligned over time.

Humans&, a new startup founded by alumni of Anthropic, Meta, OpenAI, xAI, and Google DeepMind, thinks closing this gap is the next major frontier for foundational models. The company raised this week A $480 million seed round Creating a “central nervous system” for the human-plus-AI economy. Startup’s”AI to empower humans” framing dominated early coverage, but the company’s real ambition is more novel: to create a new Foundation Model architecture designed for social intelligence, not just data retrieval or code generation.

“It looks like we’re ending the first paradigm of scaling, where question-and-answer models were trained to be very smart in certain verticals, and now we’re entering what we think is the second wave of adoption where the average consumer or user is trying to figure out what to do with all of this stuff,” Andy Peng, a former employee of Human&C, told a colleague.

Humans’ pitch focuses on helping humans in the new era of AI, going beyond the narrative that AI will take over their jobs. Whether it’s just marketing or not, timing is of the essence: companies are transitioning from chat to agent. The models are competent, but the workflows are not, and the coordination challenge remains largely unsolved. And through it all, people feel threatened and overwhelmed by AI.

The three-month-old company, like several of its peers, has managed to raise its startling seed round off the back of this philosophy and the progeny of its founding team. Humans doesn’t have a product yet, nor is it clear exactly what it might be, though the team says it could be a replacement for multiplayer or multi-user contexts like communication platforms (think Slack) or collaboration platforms (think Google Docs and Ideas). As for use cases and target audiences, the team pointed to both enterprise and consumer applications.

“We’re building a product and a model that’s focused on communication and collaboration,” Eric Zelikman, co-founder and CEO of Humans& and a former xAI researcher, told TechCrunch, noting that the product is focused on helping people work together and communicate more effectively — both with each other and with AI tools.

“Like when you have to make a big group decision, it often comes down to someone taking everyone into a room, letting everyone express their different camps, for example, what kind of logo they like,” Jelikman continued talking to his team, as they recalled the time-consuming tediousness of getting everyone to agree on a logo for a startup.

Zelikman added that the new model will be trained to ask questions in a way that feels like communicating with a friend or colleague, someone trying to get to know you. Chatbots today are programmed to constantly ask questions, but they do so without understanding the value of the questions. He says this is because they’re optimized for two things: how quickly a user likes the feedback they give, and how likely the model is to answer the questions it answers correctly.

Part of the lack of clarity about what the product is may be that people still don’t have the answer. Peng says designing the product together with the people and the model.

“Part of what we’re doing here is also making sure that as the model evolves, we’re able to co-evolve the interfaces and behaviors that the model is capable of into a product that makes sense,” he said.

What’s clear, though, is that people aren’t trying to create a new model that can plug into existing applications and collaboration tools. The startup wants to own the collaboration level.

AI plus team collaboration and productivity tools are growing hot fields – for example, startup AI note-taking app Granola $43 million round At a $250 million valuation it launched more collaborative features. Several high-profile voices are also clearly framing the next phase of AI as one of coordination and collaboration, not just automation. LinkedIn founder Reed Hoffman argued today that companies are misimplementing AI by treating it like isolated pilots, and that the real leverage is at the work coordination level — that is, how teams share knowledge and conduct meetings.

Hoffman wrote on social media. “They will be the ones to discover what should be automated, compressed or completely redesigned.”

It is the place where people want to live. The idea is that its model-slash-product will act as the “connective tissue” in any organization—be it a 10,000-person business or a family—that understands each individual’s skills, motivations, and needs, as well as how they can be balanced for the overall good.

Getting there requires rethinking how AI models are trained.

“We’re trying to train the model in a different way so that more humans and AI interact and collaborate together,” Yuchen He, a human and co-founder and former OpenAI researcher, told TechCrunch, adding that the startup’s model will also be trained using long-horizon and multi-agent reinforcement learning (RL).

Long-horizon RL means training the model to plan, operate, modify and follow over time, rather than just generating a good one-off answer. Multi-agent RL trains for environments where multiple AIs and/or humans are in the loop. Both of these ideas are gaining momentum Recent academic work As researchers push LLMs beyond chatbot responses to systems that can coordinate actions and optimize outcomes across multiple steps.

“The model has to remember about itself, about you, and the better its memory, the better the user’s understanding,” he said.

Despite the stellar crew running the show, there are plenty of risks ahead. The expensive effort of training and scaling a new model will require people and unlimited amounts of cash That means it will compete with major established players for resources including access to compute.

The top risk, though, is not to compete with people and only the world’s ideas and slack. It’s coming for AI’s top dog. And these companies are actively working on better ways to enable human collaboration on their platforms, even as they vow that AGI will soon replace economically viable work. Through Claude Cowork, Anthropic aims to optimize work-style collaboration; Gemini Workspace is embedded so AI-enabled collaboration is happening within the tools people already use; And OpenAI has recently been pitching developers on its multi-agent orchestration and workflows.

Crucially, none of the major players seem ready to rewrite a model based on social intelligence, which either gives people and a leg up or makes it an acquisition target. And with companies like Meta, OpenAI, and DeepMind finding top AI talent, M&A is definitely a risk.

Humans& has told TechCrunch that it has already turned away interested parties and is not interested in an acquisition

“We believe this is going to be a generational company, and we think these models have the potential to fundamentally change the future of how we interact,” Zelickman said. “We believe in ourselves to do this, and we have a lot of faith in the team we’ve assembled here.”

This post was published on January 22, 2026.