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Graia Recognised as a Leading Challenger in Juniper Research's AI Agents for Customer Experience Leaderboard

juniper-graia-leaderboard

 

Graia, the AI platform powering Mplus's next-generation customer experience solutions, has been recognised as a Leading Challenger in Juniper Research's latest AI Agents for Customer Experience Platforms Competitor Leaderboard.

The report evaluates vendors across product capability, market presence, and strategic positioning, identifying the companies shaping the future of customer experience technology. For Mplus, this recognition reflects something we see every day across our operations: the way enterprises deliver customer experience is changing, and the pace of that change is accelerating.
 

A Market at an Inflection Point

Juniper's research points to a significant shift underway in how enterprises approach AI in customer experience. Investment in AI agents is growing rapidly, adoption is moving from experimentation to live deployment, and multi-agent systems with genuine interoperability are becoming table stakes rather than differentiators.

New standards like Model Context Protocol (MCP) and Agent-to-Agent (A2A) communication are expanding what AI agents can do, making them easier to integrate, more scalable, and more impactful across the enterprise. This is no longer a story about isolated automation. It is about connected, intelligent systems operating across the full customer journey.
 

Why Graia Was Recognised

Juniper identifies several areas where Graia stands out from the field:

Agentic CCaaS Platform. A unified approach combining contact centre infrastructure with AI-native capabilities, removing the friction between legacy tooling and modern AI deployment.

Prebuilt AI Agent Repository. Ready-to-deploy agents that reduce technical complexity and accelerate time-to-value for enterprise clients.

Contextual, Personalised Interactions. Deep CRM integrations and a RAG-powered knowledge base that ensure AI responses are accurate, relevant, and grounded in real customer data.

Empathy Engine and Human-in-the-Loop Controls. AI that adapts to customer sentiment in real time, with built-in oversight mechanisms that keep human agents in control when it matters most.

Together, these capabilities allow organisations to scale automation without sacrificing context, accuracy, or accountability.
 

Built for Real-World Complexity

Graia was developed through the unification of Bulb Technologies, Geomant, and Buzzeasy, bringing together decades of expertise in customer engagement, contact centre operations, and enterprise AI. That foundation is what sets it apart.

The challenge facing enterprises today is not simply adopting AI. It is making AI work within the complexity of real operations: multiple channels, multiple markets, multiple languages, and strict compliance requirements. Graia is designed to operate within that reality, not just in controlled pilots or isolated use cases.

This is also why Mplus, with operations across 15+ countries and clients in 57+ countries, built Graia as the backbone of its AI-powered service delivery. We do not just recommend AI solutions. We operate them at scale.
 

Positioned for What Comes Next

Juniper notes that enterprises will increasingly demand AI agents that retain context across interactions, provide accurate and up-to-date responses, and route seamlessly between automated and human-led resolution. This is precisely where the market is heading, and it reflects the core principle behind Graia's design: AI should not just automate interactions. It should understand them, act on them, and improve them over time.
 

Looking Ahead

Being recognised as a Leading Challenger is an important milestone, but it also signals where the broader industry is going. Customer experience is moving beyond fragmented tools and reactive automation toward unified, agentic systems that combine intelligence, empathy, and execution.

That shift is already underway. Graia is built for it. And Mplus is delivering it.

Download the full Juniper Research report here.