As we get deeper into the swing of all things AI, we are left with the reality that the more value our customers can achieve, the more AI they want out of their enterprise software investments. This might be doubly true of AI applications across Customer Experience (CX) spaces like Marketing, Sales and Services. So, it should not be a big surprise that platforms at the intersection of these functions, especially those points where customers most directly interact and engage with organizations, are hungry to capitalize on any and every power-up they can capture.
Exhibit A: Hubspot’s announcement that they have agreed to acquire Frame AI, a self-described AI-powered conversation intelligence platform. The question here is…what else can Frame AI bring to the already robust customer platform outside of conversational intelligence?
What We Know About the Deal: Hubspot has signed an agreement to acquire Frame AI with the intention to integrate Frame AI’s conversational insights directly into Hubspots existing Breeze platform, Hubspot’s family of AI models and technologies that are embedded across the Hubspot solution. At the close of the acquisition, Hubspot intends for Frame AI to become a wholly owned subsidiary of Hubspot and the 60-person team HubSpot to oversee the accelerated integration. Financial arrangements were not disclosed and what is known about Frame.AI’s financial posture is limited to it being a hot start in a hot space, raising $17 million over an estimated 4 rounds of funding. Its last documented round was a Series B for $7.6 Million in late 2022.
What Makes Frame.ai so Interesting: Unlike the standard “data is the fuel for AI” pitch, Frame AI has taken the approach that real customer intelligence isn’t just found in the “obvious” places like transactional or structured data, but rather in the unstructured, complex and often “dormant data” that can unlock opportunity and advantage. Their stated differentiation is the use a “Stream-Triggered Augmented Generation” (STAG) that unlocks unstructured data from calls, emails, documents and even emails and leverages insights from this stream to train, hone and tailor a more contextual, predictive Generative AI assistant thanks to active monitoring of both structured and unstructured data across the enterprise. And while yes, the capacity to integrate unstructured data into this business graph is interesting, perhaps the more interesting aspect of this acquisition is the velocity, capacity and vector of Hubspot’s evolution of AI and Breeze’s capacity to deliver real, measurable and actionable value for their customers. Acceleration is good….being able to able to move a lot quickly is great…but having maximum impact with direction is the end game here.
For Sales and Revenue Leaders: The addition of Frame AI’s ability to parse out signals from unstructured data will be a boon to Hubspot’s sales automation capabilities in addition to its service offerings. As Hubspot looks to support the “full journey” - the signals extracted by Frame AI can power more proactive sales engagement in the initial sales, as well as throughout post-sale/customer success motions. For example, while Frame AI has identified escalation and churn potential for customer service teams, those same signals can aid sellers and customer success managers to potential positive scenarios (such as expansion opportunities) or negative ones (such as potential churn or user downgrades).
Providing these signals to revenue teams enables not only a more proactive growth mindset, but also a more predictive one. The signals extracted by Frame AI’s technology can also guide how post-sales teams engage to drive upsell and cross-sell, which not only reduces friction in the customer experience around renewals and expansion, but also reduces the time and some costs associated with post-sale engagement models.
For Marketing and Service Leaders: This addition to the Hubspot family turns up the volume on customer voice, turning these often separated, segmented and unstructured data streams into a normalized and continuous signal. For marketing and service teams, having data has never been the real problem. Being able to separate actionable signal from the buzz of customer noise has derailed slowed decision velocity, making it impossible to contextualize risk as opposed to opportunity. From personalization of marketing messages to proactive churn risk engagements in customer support, opportunity, risk, management, mitigation and lifetime value optimization feed and work from a unified framework of augmented data.
Unleashed on the data that Hubspot customers already collect and generate across the platform, these proactive tools can level-up critical insights that could easily go overlooked in the sea of dormant data. Thanks to generative AI and the augmented generation technique offered in their STAG approach, Frame can also trigger focused and contextual workflows and automations. For the Hubspot customer, this acceleration of AI capabilities could mean the difference between identifying interesting information versus acting on critical signals. But it also falls in line with Hubspot’s long standing approach of not sacrificing the quality and fidelity of a customer’s voice for the advancement or complexity of a functions processes or functional technology stacks.
What it Means for Existing Customers: Hubspot customers leveraging Breeze are well aware of the Copilot and Agentic workflows and generative capabilities that can be deployed across the platform, but will likely be eager to accelerate the onboarding of even more context and specificity thanks to the unification of Hubspot data with more sources of unstructured data. The question around customers is likely more relevant for existing Frame AI customers who may be leveraging Frame AI in their Salesforce, Braze or Twilio environments. While early indications point to Frame AI operating as a subsidiary, it is unclear in these early days if the promise of “works how and where you work” will remain post deal closing.
Parting Thoughts: Overall, the addition of Frame AI offers Hubspot users a lot of potential upside. It takes the offerings from a highly structured data-focused tool set into one that can better consume and take action on more unstructured data types. It also feeds Hubspot’s AI strategy - making existing and subsequent generative and agentic AI features more powerful as they will have a far larger and more robust pool of data on which to draw inferences and take action.
Hubspot considers itself a business scaling platform, focusing on the end value the platform will drive as opposed to the strategy or functional teams it will support to reach an end goal. Their vision of delivering tools that make business thrive is no small feat, especially in the age of AI where every advancement feels like it comes with 4x more requirements for skills, data and advanced technology that fast-growth, upstart and mid-market movers may not be able to support. Instead of biting off more tech than a company can chew, Hubspot has long focused on scaling with as opposed to scaling ahead of their customers. This acquisition falls in line with that approach, accelerating their position in AI by enhancing their embedded models and applications across the platform.
In the end, this acquisition accelerates the buildout of a robust AI framework, data repository and model suite that is driven to deliver easy out of the insanely complex. If wrangling customer voice was easy, we would have mastered it decades ago. The reality is that voice, data and extracting signal from unstructured AND structured data has been a massive exercise in patience and juggling. But AI has moved the needle more in a few years than many pundits felt would be possible and now Hubspot is taking advantage of this shift by building is a growth engine that can be driven by any number of drivers across the enterprise.
