Riverty, the fintech division of Bertelsmann, and Microsoft-focused integrator Cluster Reply have pulled off a rapid deployment of an omnichannel customer service platform—going live across eight markets and four languages in just 100 days. The system, built on Microsoft Dynamics 365, Dataverse, and Copilot Studio, is already handling voice, chat, and email interactions with AI-assisted routing and context recognition, marking a tangible step toward what Riverty calls an "AI-first, human-centric" strategy.

A 100-Day Sprint to AI-Infused Support

The project's speed is striking. Cluster Reply and Riverty delivered a production-grade contact center in roughly three months, replacing or consolidating previous systems. The core technical ingredients are all first-party Microsoft: Dynamics 365 Customer Service (specifically the Omnichannel for Customer Service module) for agent workflows, Microsoft Dataverse as the central data repository for transcripts and case context, and Microsoft Copilot Studio to author the AI agents that will eventually handle autonomous conversations. (Note: Dynamics 365 Contact Center, a newer SKU, may also be in play—the sources mention both "Dynamics 365 Customer Service" and "Dynamics 365 Contact Center" interchangeably; the practical architecture appears consistent.)

The initial rollout delivers unified queues for voice, chat, and email, giving agents a single pane of glass. Real-time dashboards and automated reporting were live from day one, providing supervisors with immediate visibility into operations. On the AI front, two capabilities are already in production: intelligent routing that reduces transfers by steering inquiries to the right queue, and automated context recognition that summarizes past interactions and prepopulates agent screens, cutting down time spent on research.

What This Deployment Delivers Today

For Riverty's millions of consumers, the most immediate change is faster, more consistent service across channels. A customer who emails and then calls won't have to repeat their issue—the unified history follows them. Agent assist features, while not fully autonomous, lighten the cognitive load on human staff, which typically leads to shorter handle times and fewer errors. The vendor reports early signs of declining request-processing times and rising customer satisfaction, though these metrics remain vendor-reported and await independent validation.

From a technical standpoint, the architecture separates transactional data (stored in Dataverse) from AI behavior (coded via Copilot Studio). This separation is critical for regulated industries: it means every AI-generated suggestion can be traced to a curated knowledge base, and hand-offs to humans follow explicit policies. Dataverse also serves as the audit trail, which will please compliance teams. Transcripts, sentiment cues, and routing signals all flow through Dataverse, creating a unified context that agents can access in real time.

Copilot Studio integration is planned as a staged rollout. Currently, the AI supports agents; later phases will introduce chatbots and voice bots that can independently resolve simple queries—like balance checks or payment due dates—while seamlessly escalating anything sensitive to a person. The staged roadmap reflects a deliberate "human-centric" approach that keeps people at the center of complex or sensitive interactions.

Why IT Leaders Should Pay Attention

If you manage a service desk in any regulated sector, Riverty's blueprint offers five immediate takeaways:

  1. Speed doesn't mean reckless. A 100-day deployment is achievable when you leverage a pre-integrated stack. Dynamics 365 plus Dataverse plus Copilot Studio eliminates the integration tax that custom-built solutions incur. The use of Microsoft-managed connectors, Entra ID for identity, and Azure security controls reduces the risk of compliance gaps.
  2. Start with agent assist, not full automation. Riverty's phased approach—agent assist → constrained chatbots → voice bots—lowers the risk of AI missteps. Humans stay in the loop until the AI proves itself in text-based channels. This is far safer than rushing into voice automation, where missteps can be more damaging to customer trust.
  3. Observability is non-negotiable. Live dashboards and automated reporting aren't just for managers; they create the telemetry needed to detect when AI answers drift or degrade. Without that data, you're flying blind. Riverty's real-time dashboards are foundational for continuous improvement and for meeting auditors' expectations.
  4. Govern the AI's behavior, not just the data. Copilot Studio agents should only pull from vetted knowledge sources. In fintech, a hallucination about a credit score or account status could trigger regulatory action. The behavioral layer must have strict confidence thresholds and automatic escalation to humans, with all decisions logged for audit.
  5. Negotiate Copilot licensing upfront. Microsoft's pricing for Copilot consumption can be opaque. Demand usage metrics, cost caps, and clear SLAs to avoid bill shock as automation scales. Some Copilot features are usage-sensitive; without contractual guardrails, costs can spiral.

The Road to Copilot-Powered Support

Riverty's decision to go all-in on Microsoft's stack didn't happen in a vacuum. The company processes tens of millions of transactions monthly and serves millions of consumers across Europe. Fragmented customer service tools were slowing agents and frustrating customers. At the same time, regulators increasingly demand auditable trails and data residency compliance—a challenge that Microsoft's first-party services, with region-specific data centers and compliance certifications, are designed to meet.

Microsoft has been aggressively positioning Copilot Studio as the low-code companion to Dynamics 365—promising that non-developers can build conversational agents with guardrails baked in. The Riverty engagement is a high-profile test of that promise. If successful, it could pave the way for broader adoption in fintech, healthcare, and other regulated verticals. The 100-day timeline also reflects Cluster Reply's expertise as a Microsoft specialist. For organizations without such a partner, a similar project might take longer. But the playbook is repeatable: baseline your current KPIs (average handle time, customer satisfaction, first-contact resolution), migrate channels in parallel, and only then layer on AI.

Action Plan: How to Replicate the Success

For IT leaders eyeing a similar transformation, here's a concrete sequence:

  • Week 1–2: Measurement baseline. Capture AHT, CSAT, FCR, and agent occupancy. You'll need these to prove value later. Engage compliance early to map data flows and retention policies.
  • Month 1: Unify channels without AI. Consolidate voice, chat, and email into Dynamics 365 Omnichannel first. Clean up knowledge bases. This alone can reduce handle times and improve agent experience.
  • Month 2: Deploy agent-assist AI. Enable automated context summaries and routing suggestions. Keep humans in the loop and monitor for accuracy. Use Copilot Studio to author these retrieval-based agents, ensuring they only source from curated, versioned knowledge.
  • Month 3: Pilot text-based chatbots. Start with non-sensitive inquiry types (e.g., "Where is my order?"). Use Copilot Studio to author and rigorously test. Set strict confidence thresholds—anything below 90% should escalate to a human.
  • Month 4–6: Expand to voice, cautiously. Voice adds complexity: authentication, emotion detection, accents. Begin with a limited set of intents and escalate quickly. Use the data from dashboards to tune the models.
  • Ongoing: Enforce governance. Regularly audit AI transcripts, update knowledge sources, and review licensing usage. Demand your SI include cost observability in the contract. Consider a dedicated AI governance board to oversee changes.

Don't skip the contractual fine print. Microsoft Copilot usage can rack up charges if every interaction triggers a generative response. Cap consumption during pilots and negotiate pricing based on resolved interactions, not per token. Ask for transparent reporting on Copilot usage to avoid surprises.

Looking Ahead: The Copilot Studio Roadmap

This deployment puts Copilot Studio under a spotlight. While it's clearly capable of powering agent-assist features today, the next 12–18 months will determine if it's truly ready for unsupervised voice automation at scale. Microsoft has indicated that future updates will bring better voice analytics, native authentication controls, and enhanced data residency options—all essential for regulated industries. Pricing and licensing models are also expected to evolve as enterprises push back on unpredictable costs.

For now, the Riverty case provides a grounded, real-world example of AI-first customer service that doesn't sacrifice human empathy. It's not a marketing demo; it's in production, serving real customers, with measurable (though vendor-reported) improvements in request processing times and satisfaction scores. As independent validation emerges, expect more financial services firms to follow suit. Timo Reis, Global Operations Excellence Lead at Riverty, characterizes the platform as a milestone in the company's AI journey, emphasizing a future-proof architecture with Copilot at its core.