Honeyjar uses AI to scale PR expertise for non-experts

Overview

Artificial intelligence is increasingly being deployed to solve entrenched inefficiencies in traditional industries, and public relations is no exception. A new startup called Honeyjar is aiming to democratize access to high-level communications strategy, a resource that has historically been reserved for large corporations with deep pockets or specialized agencies.

The company, which is currently showcasing its platform at TechCrunch Disrupt as part of the Startup Battlefield 200, seeks to scale the judgment and expertise of veteran PR professionals for a broader audience. This includes founders, marketers, and other professionals who lack formal communications training but face significant pressure to manage their public narrative effectively.

By leveraging AI, Honeyjar attempts to bridge the gap between manual, labor-intensive PR processes and the need for strategic, timely outreach. The platform automates critical workflows such as media list building, journalist identification, and draft writing, while emphasizing that human judgment remains central to the decision-making process.

Scaling Expertise Through Automation

The core mission of Honeyjar is rooted in the experience of its founders, CEO Michelle Masek and CCO Nadia Jamshidi. Both veterans with decades of experience in in-house communications and agency work, they recognized a consistent bottleneck in the industry: the inability to scale senior-level intuition.

Masek previously served as senior vice president of marketing and communications for Obvious Ventures, where she supported over 100 portfolio companies. She noted that founders frequently asked for guidance on how and when to approach media, yet there was no efficient way to provide that mentorship at scale.

"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?"

Honeyjar addresses this by automating several key functions. The platform can identify promising speaking opportunities, draft press announcements, and find the most relevant journalists to pitch. However, the founders insist the tool goes beyond simple task automation.

Jamshidi explained that while features like scanning news, tracking coverage, and surfacing opportunities are important, they represent only one component of the system. The broader vision involves integrating signals, context, strategy, timing, and execution into a unified communications workflow.

This focus on workflow integration is designed to serve not just startup founders, but also what Masek describes as "millions of unassigned communicators." These are individuals such as school superintendents, sports team leaders, authors, and investors who handle communications responsibilities without holding the official title.

Beyond Press Releases: The Role of Judgment

A common criticism of AI in media relations is the potential for flooding journalists’ inboxes with low-quality, generic content. Honeyjar’s leadership acknowledges this risk and has designed its product to mitigate it through encoded judgment rather than blind automation.

The company is developing a broader initiative called the Comms Lab, which trains its AI on the decision-making patterns of experienced PR professionals. According to Jamshidi, this involves teaching the system to understand a company’s goals, internal dynamics, and external context.

Judgment, in this framework, is defined as knowing what to do, what to avoid, when to act, and how to adapt. In some instances, the system may advise a founder that they are not yet ready for media coverage, prioritizing long-term credibility over immediate attention.

Masek emphasized that Honeyjar is not intended to replace PR firms or in-house teams. Instead, the tool is designed to make existing professionals more effective. For example, it could allow a solo PR practitioner to take on additional clients without incurring proportional scaling costs.

The platform requires users to review and approve all outputs before they are sent. While Honeyjar can draft pitch emails or social media posts in a customer’s specific voice, the human user must ultimately hit send or publish.

"We never want a world where the human is removed from the loop."

Masek argued that this human-in-the-loop approach could actually improve the quality of pitches journalists receive. By combining AI efficiency with human oversight, the goal is to ensure that reporters hear from experts directly, rather than from automated spam bots.

Market Reception and Future Outlook

Since opening its waitlist, Honeyjar has seen significant early interest. Masek reported that the platform received 10,000 signups within its first 24 hours, indicating a strong demand for accessible PR tools among non-experts.

Beta testing has included a diverse range of organizations, from tech startups like Coco Robotics and social network Nextdoor, to venture capital firms such as Bloomberg Beta. Agencies including Mission North and Full Picture are also testing the platform, suggesting its utility spans both independent practitioners and established firms.

Despite the promise of increased efficiency, the broader implications for the media landscape remain a subject of debate. Journalists have long complained about the volume of automated pitches they receive daily. The introduction of more sophisticated AI tools raises concerns that the noise-to-signal ratio in media inboxes could worsen.

However, Honeyjar’s founders believe that by encoding better judgment into the automation process, they can contribute to a healthier ecosystem. They envision a future where the volume of credible, well-targeted pitches increases, allowing journalists to connect more meaningfully with sources who have genuine expertise.

As AI continues to permeate various professional sectors, Honeyjar represents a targeted attempt to preserve human strategic input while leveraging machine speed. Whether this model can overcome the skepticism of journalists and deliver tangible value for non-expert communicators will depend on its ability to consistently produce high-quality, context-aware results.