When we started building our Artificial Intelligence Buyout (AIBO) strategy, we began with a simple premise. The first months after an acquisition shouldn’t be spent only integrating finance, technology and operations. They should also be spent finding growth.
Traditional holding companies often create value through consolidation, cost reduction and financial discipline. Those levers are still important. AIBO adds a shared intelligence layer designed to help each company understand its market, make stronger decisions and find opportunities to grow earlier.
Today, that model is taking shape across five operating companies: RAD Amplify, Lickly, AVC, Atomic Capital and Altivera Vision.
Marketing Data Gives Us an Early Advantage
Marketing produces one of the fastest and clearest feedback loops in business. You can see which audiences responded, which ideas earned attention, which content moved people to act and where budget was wasted.
RAD Intel’s platform analyzes billions of audience and content data points across online conversations. It helps teams understand what people care about, identify the language shaping their decisions and predict which audiences, creators and ideas are most likely to perform.
That intelligence can shape a company’s marketing before more money is spent. Once the work is in market, performance creates another round of learning.
We proved the model inside RAD Intel first. Our focused marketing team used the platform to identify the right audiences, understand the conversations influencing their decisions and build content around the ideas most likely to resonate. That Human + AI approach helped us support a $62 million raise in eight months.
AI accelerated the research, testing and learning. Our team brought the judgment, creativity and human voice.
How AIBO Changes the Acquisition Filter
That experience influences how we evaluate companies today. We’re looking for strong businesses with customers, revenue, category expertise and a model that already works. We also want to understand what our intelligence and shared growth infrastructure could unlock.
Alan Arnstein, our Chief Business Development Officer, leads that work across the AIBO strategy. “We evaluate every opportunity through one lens: does this create measurable, repeatable advantage across the platform?” said Arnstein.
That question takes us beyond whether a company is financially attractive. We’re looking at where better audience intelligence, faster learning and stronger marketing decisions could create additional growth. We’re also looking at what the company’s expertise and market knowledge could contribute to the broader portfolio.
Five Companies Putting the Model to Work
Within marketing, RAD Amplify uses predictive intelligence to shape creator campaigns for enterprise brands and agencies. Lickly puts Decision Intelligence directly into the hands of marketing teams, helping them predict what to do next, defend the decision and shorten planning cycles. AVC adds more than two decades of multicultural marketing experience and a deeper understanding of how brands earn relevance across diverse audiences.
Atomic Capital extends the application of intelligence into crypto-based securities and emerging financial markets. Altivera Vision will apply the same decision discipline across vision care, connecting patient acquisition, consultation and scheduling while physicians remain in control.
Each company has its own ICPs, leadership and expertise. RAD Intel surrounds that core with shared technology, marketing intelligence, infrastructure and Human + AI capability.
Then we compound everything across the portfolio, including the technology, tested workflows and what we learn about turning intelligence into stronger decisions.
Growth Is Part of Every Integration Plan
Cost discipline, financial controls and efficient infrastructure will always be part of building a strong portfolio. AIBO expands the value-creation plan to include audience growth, customer acquisition, conversion and marketing performance from the beginning.
That gives us five different proving grounds for the model. Every company puts the intelligence to work against a different set of decisions. Each outcome gives us another opportunity to improve the platform and carry useful learning forward.
Every company we add should become stronger while making the intelligence layer smarter. That compounding effect is central to the AIBO strategy.
