Topline · 10 Sep 2026 · From the week of 7 September
SPOTLIGHT: Skipping the SMB Trap and Building for Big Brands | Matt Allison, CEO & Founder @ Handraise
These are notes on the conversation, checked against its transcript. The episode itself has the full discussion.
In brief
Matt Allison, CEO and co-founder of Handraise, joins hosts Sam Jacobs and AJ (CEO of QuotaPath and former co-founder of TrendKite) for a Topline Spotlight episode. He describes Handraise as an AI-based media intelligence platform and explains why it is selling to enterprise brands from the start rather than SMBs, drawing on TrendKite's churn and contract-value history. He argues that building a product enterprises will pay $30K+ for takes patience and discipline, and he discusses building AI-first, keeping models interchangeable, and resisting pressure to grow at hypergrowth pace.
For founders
- Handraise is building for $30K+ enterprise accounts from day one, drawing on TrendKite data that showed its smallest accounts churned heavily while its top tier retained best in class.
- Matt says building a product substantial enough to command enterprise pricing takes sustained discipline, and that investors need the same stomach for slower growth.
- Handraise picks AI models by testing which performs best on F1 score and swapping in the winner rather than building the company around one model provider.
- An ML filter runs before any AI model to strip out noise such as sidelinks, which Matt says keeps AI costs workable while margins stay good.
- Matt says Handraise's AI-first build lets a 12-person team ship features more sophisticated than TrendKite's product after seven years of development.
For revenue leaders
- TrendKite's lowest-tier accounts, around $2K to $5K ARR, had very high churn, while its $30K+ tier had best-in-class retention, which is why Handraise targets enterprise accounts.
- Handraise's ideal customer is senior and executive communications leadership, such as heads of comms, at large complex organizations with a lot of news.
- Matt plans a highly focused, high-quality outreach motion using product screenshots rather than mass AI-generated outreach, though he says the team is still learning what works.
- Matt said TrendKite's average contract value grew from roughly $2K to $5K in year one to about $25K when it exited in 2019, and he said AJ could correct the figures.
What was said 18, most useful first
At TrendKite, the smallest accounts churned heavily while the $30K+ tier retained best in class. Listen
Matt said TrendKite tiered its accounts from tier one to tier five by revenue band. Its tier five accounts, which were around $2K to $5K ARR deals, had very high churn, while its tier one accounts at $30K plus had best-in-class retention. This experience is why Handraise is trying to sell to enterprise accounts from day one.
“our Tier 5 accounts, which were our call them like our 2 to 5000 ARR deals had a very, very high rate of churn. And then our tier one, which were 30k plus, we had best in class retention around those.”
Listen to the episode Retention & customer success Link to this
Handraise is selling to enterprise from day one, aiming to command $30K+ checks from large companies. Listen
Matt said the core problem is building a product well positioned for enterprise accounts, selling to them from the start, and building something valuable enough to command a $30K-plus check. He contrasted this with TrendKite, which sold many small deals and ended up with customers whose businesses and demands differed from enterprise companies. He described it as a deliberate choice to skip the SMB trap.
“how do we sell to those enterprise accounts day one and build something that's valuable enough where, you know, we can demand a, or command like a, you know, 30k plus check from those types of companies?”
TrendKite's first round was a $1.5M Series A on a $4.7M post-money valuation, with no pre-seed or seed before it. Listen
AJ said TrendKite called its first round a Series A, which he said they should not have done, since there was no pre-seed or seed round before it. The round was $1.5 million on a $4.7 million post-money valuation in 2012. Matt said that in the early days the company's growth rate always felt one round behind, so they had to convince investors that what they were building was meaningful.
“our Series A was our first round. We didn't have a pre seed or a seed. We called it a Series A, which we should not have done. And it was a $1.5 million round on a $4.7 million post money valuation 2012.”
An ML filter runs before the AI model to remove noise such as sidelinks, which keeps AI costs manageable. Listen
Matt said running every piece of content through an AI model would be very expensive, so Handraise runs an ML process first to remove content like sidelinks, which he said were nearly impossible to filter out in the old world. He said isolating the problem to a smaller data set makes the cost workable, and that they still pull pretty good margins.
“So you know, if we ran every single piece of content through an AI model to it, it'd be really expensive. So we have, you know, an ML process that we run first.”
Handraise will not grow from zero to $100M in under a year, and that this requires investors with the same patience. Listen
Matt said building enterprise use cases requires a substantial amount of software to crawl and make sense of global news. He said the team and its investors need the stomach to stand their ground, because Handraise will not go from zero to a million to 10 million to 100 million in less than a year as some companies are doing. He called it a different business.
“we're not going to see us go from, you know, zero to a million to 10 million to 100 million in less than a year, like you're starting to see with some of these companies.”
TrendKite's average contract value rose from roughly $2K to $5K in year one to about $25K by its 2019 exit. Listen
Matt gave the progression as roughly $2,000 to $5,000 in the first year, $8,000 to $10,000 in the second, then $12,000 and $15,000, with deals right around $25,000 when TrendKite exited in 2019. He said AJ could correct him on the figures. He was describing how the early small deals brought in customers with very different demands from enterprise companies.
“our ACVs went from like probably around 2000 to $5000 the first year up to about 8 to $10,000 the second year”
Enterprise go-to-market requires the patience and stomach not to sell aggressively from day one. Listen
Matt contrasted Handraise with TrendKite, which he called a sales machine from day one, with he and AJ cold call selling before the product was ready. For Handraise he framed the key question as whether the team can resist aggressive selling early on. He said the answer depends on the investors as well as the team having the stomach for slower growth.
“can we have the patience and do we have the stomach to not go out and sell deals like crazy Day one? I mean Trend Kite was a sales machine from day one.”
Handraise has about five high-quality customers after turning on its revenue motion a couple of months before recording. Listen
Matt said Handraise is still a seed-stage company that has raised $6.4 million in total. He named Walgreens, the Clooney Foundation and Hershey among the companies it works with, and said Handraise had just signed a deal with Apotex, which he described as Canada's largest pharmaceutical company.
“We are still a seed round company. We raised $6.4 million total. We just turned on our revenue motion a couple months ago.”
Handraise's ideal customer is senior communications leadership at large, complex organizations with a lot of news. Listen
Matt said Handraise is still working out its ICP, which typically means senior comms directors, executive comms directors or heads of comms at the world's largest companies. He said moving upstream was a key learning because these organizations are large, sophisticated communications operations that support the business.
“You know, it's typically senior comms directors, executive comms directors, maybe head of comms at some of the world's largest companies where they have a lot of news.”
Investors often underestimate PR software because they picture PR as people pitching stories. Listen
Matt said that when VCs hear about PR technology and the TrendKite exit, they often think of the industry as a bunch of PR people pitching stories. He said that once you get into large organizations, comms teams are sophisticated machines that support the business, including work on political and policy change.
“oftentimes they think of our industry as, you know, a bunch of PR people running around just pitching story.”
Being AI-first means AI is built into every feature from the ground up, not just used as a coding aid. Listen
Matt said Handraise uses AI co-pilots, but the bigger change is that as the team builds from the ground up, AI is infused in every single thing it builds. He said the advantage is in the technology the team can use rather than in having superpower engineering teams.
“as we build things from the ground up, there is AI infused in every single thing that we build.”
Handraise is not dependent on any single model, testing which performs best on F1 score and plugging in the winner. Listen
Matt said Handraise is a team of 12 that daisy-chains models together, using some of its own in-house ML alongside outside models. The team constantly tests which model performs best for specific tasks, judged on F1 score, and plugs in the most performant one over time. He said model costs are dropping quickly.
“And we're, we're not dependent on any singular model. They're able to see which one is the most performant and then they're able to just plug that in over time.”
Handraise plans focused outreach with product screenshots instead of AI-generated mass outreach, though Matt says they are still learning. Listen
Matt said TrendKite started with cold call selling and later added an inbound motion. For Handraise he expects much more focused, high-quality outreach that uses screenshots of the product to send real value, rather than throwing everything into an AI machine on day one. He said the company is still learning what will work well.
“And I think for us, it's going to just be like much more of a highly focused, high quality outreach where we're using screenshots of the product and trying to send real value versus anything that we're just, at least on day one, throwing into an AI machine to call it spam in the tam.”
Existing media monitoring tools leave data dirty, forcing teams to export it and clean it by hand. Listen
Matt said users of tools such as Meltwater, Cision and Muck Rack often get data that is dirty, so they export it to CSV or spreadsheets and clean thousands of rows of news articles every week, month or quarter. He said this manual work is the problem Handraise is using AI to solve.
“The data ends up being really dirty, so they have to export it to like a CSV file, Google sheets, Excel, and then they have to wrangle this data around, clean it.”
Handraise's current product is more sophisticated than TrendKite's was after seven years of development. Listen
Matt said Handraise's product is dramatically more sophisticated at this stage than TrendKite's product was after seven years. He attributed this less to supercharged engineers and more to being AI-first, meaning AI is infused in everything the team builds from the ground up, with the technology unlocking value at an astonishing rate.
“I would say that our product today is not even close. Like, it's dramatically more sophisticated at this stage in the game than our. Like, I would say it's more sophisticated than our TrendKite product was after seven years of on that thing.”
Handraise's narrative clusters generate a summary and a why-it-matters section with a single button press. Listen
Matt described pressing a button on a narrative cluster to generate a summary in Axios-style brevity formatting that reads all the coverage and says what to know. It then looks more broadly at the news about the company and provides a 'why it matters' section. He said building something like this at TrendKite would have taken many months and still would not have hit today's quality bar.
“We're able to just press a button and it generates a summary of the narrative that gives an Axios Smart brevity style formatting on that thing”
Handraise runs with a team of 12, including two AI engineers that Matt describes as industry leading. Listen
Matt said the team has 12 people, and that two of them are industry-leading AI engineers. He said one went through Harvard and helped build AI at Google, and the other studied and trained at Oxford.
“So our team, we're a team of 12 people today. Two people on that team, I would say are like industry leading AI engineers.”
A partner at Mike Maples's firm asked him to picture Handraise as a trillion-dollar business. Listen
Matt said that after closing the first financing with Mike Maples's firm, one of its partners asked him over dinner what Handraise would look like as a trillion-dollar business. He said he first chuckled, then realized the question was dead serious. He said that for those investors, thinking big and trying to build a legendary company is serious business.
“he asked, hey Matt, like you should start thinking about like if, if hand raise was going to be a trillion dollar business, like what would that look like?”