AI browsers were all the rage in 2025. Companies large and small tried to build browsers that baked in AI in an effort to own the interface people use to browse the internet.

How the turns have tabled. Today, OpenAI’s Atlas is history, and The Browser Company sold to Atlassian, with its Dia browser now focusing on productivity use cases. Firefox tried to strike a balance in its own AI efforts by providing an off-switch, but it got shouted at anyway.

This year, the focus has shifted to agents and automation. Startups like Strawberry, Browser Use, and Aside are building browsers with an agentic slant, and even Perplexity’s Comet has moved towards providing browser agents.

Amid this change, a startup called Polar has come out with an AI-first browser aimed at knowledge workers, and it has now raised a $5.7 million seed round led by Madrona.

CEO, Kevin Jiang, who previously worked at Perplexity on Comet, said the first wave of AI browsers aimed to change default search for users and have them chat with tabs for doing tasks like travel booking, which wasn’t a strong long-term proposition.

“If you think about end-user consumers, they don’t book a flight or make a reservation every day or every week. There wasn’t a strong pull for mass consumers to go to an AI browser and find value in it. That’s why our AI browser is not focused at all on mass consumers. We’re focused on where we think browser agents are actually valuable, which is knowledge work,” Jiang told TechCrunch.

With Polar, users can schedule workflows, save prompts and assign tasks to agents based on their open tabs. The company says the browser can be easily used by non-technical users, and can help with work like sales, recruitment, marketing, research and business operations.

The browser itself is free to use, and you get a few daily credits to spend on AI tasks. Users that want higher credit limits can pay for subscription plans starting from $20 per month.

Polar says most of its current user base just uses its browser for automating tasks while using another browser as their daily driver. The startup’s goal is to become a tool for automation, and it believes that the browser is currently the best way to do it. Still, it is open to exploring other avenues, such as computer use.

Sabrina Albert, a partner at Madrona, said automating tasks for knowledge workers is a huge market.

“I think that the hard part is building really reliable agentic work on the open, logged-in web. Building a web browser has a whole set of different advantages of understanding how users interact and engage with websites. Plus, they are logged into most of these websites, giving the tool access to services they use the most,” she said over a call.

The round also saw participation from ex-GitHub CEO Thomas Dohmke, Phia founder Phoebe Gates, Modal CEO Erik Bernhardsson, Flapping Airplanes co-founder Benjamin Spector, Etched co-founder Rob Wachen, and Fundamental Research Labs co-founder and CEO Robert Yang.

Encore AI, a startup that studies companies’ customer interactions to train and deploy AI voice agents that can work alongside customer support and sales teams, or operate autonomously, has raised $30 million in a Series A round led by Team8.

Founded in 2022 as Insait IO by CEO Dvir Ginzburg, the company started out building recommendation software for financial advisers and relationship managers. Now rebranded as Encore AI, the startup has expanded that system into a platform that analyzes conversations between a company’s employees and customers to identify which approaches resulted in successful outcomes, and uses those findings to train its AI agents.

The result, according to Ginzburg, is an AI agent that leverages the strongest parts of the playbooks used by an organization’s employees.

“Sometimes our agents even tell the jokes that the relationship managers are telling, or give the anecdotes or examples that the relationship managers are giving, because we literally run by the playbooks that we see working […] The agent we build is a package of many different playbooks that have worked throughout the process,” he told TechCrunch in an exclusive interview.

Ginzburg calls the process “interaction mining.” The company’s platform collects call recordings, emails, text messages, and connects that info with CRM systems. It then divides the customer interactions into stages and tries to find out which parts of a conversation helped move the process along, and which failed.

This lets Encore’s agents, and consequently its customers, learn what works best for any particular client or interaction, as different employees may be either more or less effective at different points during a sales or customer success process, Ginzburg told TechCrunch.

The company’s platform also lets companies identify where their existing customer support and sales processes are falling short, identify inefficiencies and friction points, and find key issues.

Encore says its agents can communicate directly with customers by voice or text, as well as act as assistants to employees, recommending responses and tactics during conversations.

The company has more than 40 enterprise customers globally, the majority of which are financial institutions, according to Ginzburg. He said Encore’s annual recurring revenue has increased more than 5x since it raised its seed round less than 18 months ago, though he declined to disclose exact revenue numbers or valuation.

Encore’s early to this market, but its share may become harder to defend as large CRM providers like Salesforce, SAP, Zoho, and HubSpot can build similar AI capabilities around their customers’ data. But Ginzburg contends that access to data alone isn’t enough, as established vendors would need to overhaul their processes to make historical customer conversations the foundation of their agents like Encore does.

“The biggest players that we are competing against, they don’t see [conversational] history as a data point that they are utilizing. For them to start asking for conversational data with their current employees will require changing their entire implementation stack and technological stack,” he said.

Planven, Lukatz and Garage also participated in the round, as did some banks and insurers. Encore said some of the financial institutions participating in the round first used its product before deciding to invest.

The startup plans to use proceeds from the Series A to expand its U.S. sales operations and deploy its platform with more large financial institutions.

DoorDash is building a drone delivery business, including its own aircraft, as part of an effort developed by its robotics and autonomy team, which will eventually operate within the company’s delivery app.

The company unveiled the new business, called DoorDash Air, after receiving a Part 135 air carrier certification from the U.S. Federal Aviation Administration. The certification allows the company to legally operate a commercial drone delivery service in the United States.

This does not mean DoorDash’s custom-built drones will be delivering burritos tomorrow, or even next month. The company didn’t provide a detailed timeline for when its aircraft would be used in operations. But before they do, it will likely begin with limited pilot programs in which the unmanned aircraft will travel short distances while remaining within the line of sight of the operator.

If DoorDash wants its drones to fly autonomously over longer distances, it will need the FAA to approve its Beyond Visual Line of Sight technology, a certification that companies like Amazon, Wing and Zipline have received in recent years.

Despite the new program, the food and grocery delivery company is maintaining its existing partnerships with Wing and Flytrex. DoorDash partnered with Alphabet’s Wing in 2022 for a drone delivery program in Australia, later expanded the partnership to a couple of U.S. cities, including Dallas-Fort Worth, in 2024.

DoorDash Air was developed within DoorDash Labs, the R&D team behind Dot, the autonomous sidewalk delivery bot the company introduced in September 2025. The delivery bot is now operating in Phoenix suburbs of Tempe, Mesa, Gilbert, and Chandler as well as in Fremont, California.

The company’s foray into sidewalk bots and drones may seem well outside its core business model — an app that connects restaurants and customers with contractors who pick up food and deliver it to people’s doors. But DoorDash’s co-founder and chief product officer Stanley Tang said there is a common thread.

“We didn’t start with the question, “What’s the coolest autonomous tech we could make?” We started from first principles: What’s the actual customer problem that needs to be solved?” Tang wrote in a blog post on Wednesday announcing DoorDash Air.

In the company’s view, drones and sidewalk bots are part of the broader delivery network it is building.

The physical hardware — for instance, a 350-pound sidewalk bot or a drone — is important to this expanded view. But Tang argues that the operating system, particularly the software that can correctly determine what mode is used to deliver that burrito, sushi or pad thai, is just as critical.

DoorDash Labs has already developed software, called the Autonomous Delivery Platform, to handle the coordination challenge, according to Tang, and this operating system works with Dot, human delivery drivers and soon, the drone.

He noted that the company is tackling the full stack of challenges, from hardware and embedded systems to routing algorithms, and deciding in real-time whether human drivers, drones, or a sidewalk bot is the best option to dispatch a delivery.

This complexity was part of Tang’s recruitment pitch to engineering hires in the blog post.

“Most autonomy companies work on one layer. At DoorDash, you’re working on all of them simultaneously; nobody else is running all these systems on one network,” he wrote. “DoorDash is where the most interesting problems in autonomy are being solved today.”