Honeyjar offers AI tools to improve PR and comms at every company; plus, WindBorne wins a hefty US Air Force contract

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1:13That's Framer.com slash tcstartups. Rules and restrictions may apply. Journalists, entrepreneurs, and even some public relations professionals will tell you that the PR process is broken. But could AI actually make things better? Honeyjar, which will be attending this week's TechCrunch Disrupt as part of the Startup Battlefield 200, wants to use AI to make the expertise and judgment of the best PR pros available to everyone, including founders who have no idea where to start. The startup's founders, CEO Michelle Masik and CCO Nadia Jamschidi, certainly fit the bill when it comes to PR expertise.

1:55They've both spent decades in the field doing in-house communications and working at agencies. Masik recently served as Senior Vice President of Marketing and Communications for Ev Williams' venture firm, Obvious Venture. There was a question that she kept asking herself. Is there a way to scale the senior-level expertise into AI in a way that actually helps users do the work of comms in the proactive and skilled way that we do? Honey Jar is her answer to that question. It automates processes like writing announcements, finding the best journalists to pitch, and identifying the most promising speaking opportunities.

2:36But Jamshidi says that Honey Jar's vision goes beyond getting press coverage and beyond specific AI tools. Honey Jar can find reporters, build media lists, scan news and social, track coverage and surface opportunities. Those capabilities are important, but they are just one piece of what we're building. The bigger idea is bringing the whole communications workflow together, signals, context, strategy, judgment, timing, and execution. And it's not just for founders. Masik said that she's come to realize there are millions and millions of unassigned communicators responsible for the work of comms.

3:15They don't have the title of comms, but they are marketers, investors, authors, creators, school superintendents, sports team leaders. It's incredibly horizontal, she said. This need to nail strategic communications. It's always passed around, but the problems are very often not solved. Now, Honey Jar is not trying to replace PR professionals. Masik said that she and Jamshidi built the tool they wanted to use themselves. She argues that Honeyjar can make PR firms and in-house comms teams more effective, while allowing individual PR practitioners to take on that third client without any scaling cost.

3:55When Honeyjar opened its waitlist, it received 10 ,000 signups in the first 24 hours. Beta testers include Nextdoor, tech startup Coco Robotics, investor Bloomberg Beta, and agencies Mission North and Full Picture. That sounds promising for companies looking to get more attention, but it could be a nightmare for journalists who receive more pitches than they can respond to, many of which are written by AI chatbots. Masik said, We never want a world where the human is removed from the loop, and that's also where judgment is key. Masik said she and Jamshidi tried to infuse and encode Honey Jar with their wisdom.

4:37Through a broader initiative called the Comms Lab, they are now training the product on the judgment of other PR pros as well. For us, judgment is knowing what to do, what not to do, when to act, and how to adapt to the situation, Jamshidi said. That comes from understanding a company's goals and priorities, what's happening inside and outside the organization, and knowing what to say to whom, where, and when. In some cases, Masic said Honey Jar might even tell a founder that they are simply not ready for coverage. We hear from reporters all the time who want better pitches, who want to hear from experts directly.

5:14We actually see a future where there are more credible pitches in your inbox from sources who you actually want to hear from. The U.S. Air Force will buy data collected by Windborne Systems' fleet of autonomous weather balloons under a new contract that could be worth nearly$50 million to the startup. Windborne currently has about 700 weather balloons flying around the globe, collecting atmospheric sensor readings that the company sells to customers and also feeds into its own AI weather forecasting model. Windborn, founded in 2015 and based in Redwood City, California, is one of the first organizations to directly feed empirical data into a deep learning weather model.

6:02The company has worked closely with the U.S. government, particularly the National Weather Service and the U.S. Air Force and Navy, but this is the single largest contract the company has participated in. The contract is worth up to$49 million, but the Air Force pays only as it needs data. It can place orders for specific regions at specific times. So far, it has ordered$1.7 million worth, and executives expect more orders to follow. Windborn co-founder and CTO Andrei Sushko told TechCrunch, this is largely a vehicle through which continued growth of the Constellation can be supported, as well as some work on research and development to continue to improve the hardware and performance of the balloons.

6:48He added that the contract, which was awarded without competitive bidding, is a determination by the government that for this capability of collecting global data, that Windborne was the only company able to provide it in the way that met their needs for their operations. Windborn CEO John Dean told TechCrunch in August that the company had raised a$37 million Series B round to continue scaling its business. Earlier this summer, the company released the latest version of its forecasting model, WeatherMesh 6, which it says provides more accurate forecasts than the traditional model run by the European Center for Medium-Range Weather Forecasts, which simulates the atmosphere using the laws of physics.

7:32Since the arrival of transformer model architectures and the ECMWF's release of a massive weather dataset a few years ago, AI weather forecasting has become one of the more productive uses of deep learning technology. Meteorologists previously relied on expensive supercomputers running detailed equations that approximate how the atmosphere behaves. Now, end-to-end learning can ingest decades of weather data and issue predictions more quickly. Models built by frontier labs and government agencies are proving more accurate than traditional forecasts, although it is still a jagged frontier with both types of forecasts required to enable useful understanding of the weather.

8:16Google DeepMind's latest weather model offers important new capabilities, and its cyclone forecasting tools are becoming increasingly central to how the U.S. government responds to hurricane season. In August, Windborn became the first organization to send an unpowered flight system, one with no engine, to collect data in the eye of a typhoon. The company maneuvers its balloons by adjusting their altitude, bleeding air, or dropping sand carried as ballast to send the vehicles into winds that take them where they need to go. Sushko said, that's a pretty novel step, and the two ingredients for that are, one, having good wind and weather models and knowing how to navigate them, and two, having a large enough constellation that you have balloons in the right places.

9:02It's one of the first times that a deep learning model was used for actual operational decisions. That's all for now. For the latest in startup tech news, go to TechCrunch.com.

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