As a rule, people who offer you the ‘best of both worlds’ usually can’t be trusted.
Too often, it’s a brand flogging their new ‘healthy’, sugar-free dessert, with the ‘same great taste’… which never has the same great taste. Or, it’s the receptionist trying to convince you that the room with a partial view of the car park and an imperceptibly bigger bathroom is a better deal than the one with the sea view that you’d originally booked.
However, hybrid AI might be the ‘best of both worlds’ offering that bucks the trend.
Indeed, for enterprises navigating AI in customer experience, the conversation is shifting. It’s no longer about picking between curated knowledge bases and generative AI.
Increasingly, the question is how to combine them to deliver support that’s safe, accurate, and scalable.
“The big issue in AI isn’t necessarily the technology itself,” says Gintautas Miliauskas, Mavenoid CEO and Co-Founder.
It’s about trust, both from the customer and sometimes even from the agent. People don’t mind talking to bots as long as they know who, or what, they’re talking to
Hybrid AI addresses that head-on. It blends the flexibility of generative models with the reliability of curated content.
For enterprises, that means broad coverage without sacrificing control over tone, messaging, and compliance.
Coverage and Accuracy: The Best of Both Worlds
One of the biggest advantages of hybrid AI is its ability to deliver breadth and precision. Generative AI can interpret free-text questions and respond conversationally, while curated content makes sure the answer is accurate, brand-approved, and auditable.
“If a user comes in with a free-text question, we can take them to a generative response, a guided response, or ask follow-up questions,” Gintautas explains.
“Either way, we don’t make the user choose the right path; they don’t need to know how to prompt the AI effectively.
“We take them where they need to go, providing images, diagrams, and escalation paths where human support is required.”
This results in fewer errors, less back-and-forth, and more consistent outcomes, which is particularly important for enterprises managing multiple product SKUs, where even a simple misstep, like an incorrect serial number, can cause costly delays. Hybrid AI helps prevent that.
Trust and Transparency
For Gintautas, although many of the headlines seem to focus on the relationship between trust and AI, in his experience, it’s “less about trust in AI, and more about trust in brands.
For example, a bot that looks the same across multiple companies can appear lazy. “Customers want the brand’s identity, not just a generic interface,” he explains.
Hybrid AI allows brands to maintain personality and clarity while being upfront about AI involvement.
This honestly has the potential to allow organizations to build confidence, improve CSAT, and encourage repeat engagement.
Moreover, for large-scale enterprise organizations, hybrid AI can go beyond support; it can also assist with governance, compliance, and sustainable ROI.
Courtney highlights how the approach is “giving brands back the control they need, but the scalability they desperately require.
Beyond support, it opens opportunities to boost revenue, conversion, and loyalty; all areas CX leaders care about, without being stuck in tickets and call queues
With legislation like the AI Regulation Act adding further pressure, enterprises need to prioritize vendors that can provide secure, compliant AI-powered solutions.
From Explaining to Resolving
Another integral step to building and maintaining trust in your AI offerings is by actually resolving issues with them.
While ‘resolving customer queries’ may sound like the first entry in ‘The Idiot’s Guide to Customer Experience’, AI has a track record of being very good at explaining problems, but less so at solving them.
“Previously, there’s been a lot of onus on the customer to come to a brand with a problem,” Gintautas says.
“Now, we can detect the right moment to explain, guide, or act. For example, with Husqvarna [a customer of Mavenoid], proactive IoT connectivity allows a customer to receive an error notification directly on their device, click through, and immediately reach the solution.”
This approach cuts downtime and frustration, and often strengthens loyalty. Customers who have problems resolved efficiently are more likely to stick with the product.
Multimodal AI: Seeing is Believing
Another, more specific, example of Mavenoid’s Hybrid AI solutions is its multimodal approach.
In short, multimodal combines voice, visuals, and messaging to make it easier for customers and agents to solve queries.
“Text alone isn’t helpful in many scenarios,” Gintautas explains.
When a customer points to a problem via photo or video, AI can provide step-by-step instructions in real time. It’s like having a technician in your pocket
A Future Built on Hybrid AI
As customer expectations rise, hybrid AI shows that safety, accuracy, and scale don’t have to be compromises.
“Hybrid AI isn’t just about technology; it’s about responsibility,” Gintautas says.
“It’s about orchestrating experiences that meet customers where they are, give them control, and deliver outcomes they actually care about.”
Hmmm, that sounds suspiciously like a ‘best of both worlds’ scenario.
You can learn more about Mavenoid’s hybrid AI approach by checking out this article.
You can also discover the company’s full suite of solutions and services by visiting the website today.
