Enhanced Customer Experience through a Modern Data Platform
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InConcert is a trusted technology partner. Leader in Latin America and Spain in contact center solutions that support businesses through every stage of their customer experience (CX) transformation. Their comprehensive omnichannel platform integrates key solutions including cloud contact centers (InConnect), virtual agents powered by Agentic AI (InAgent), marketing automation and CRM (InFunnel), quality management and speech analytics (InSpeech), and workforce management (InTeam). InConnect centralizes communication across phone, chat, email, SMS, WhatsApp, and social media to streamline operations and enhance CX.
The Challenge
InConcert set out to modernize its data platform to support rapid growth and richer customer experiences, but its existing setup was straining under heavier workloads. Reporting tables consumed excessive resources to collect, process, and store data, driving up costs and delaying access to insights. Real-time supervision was limited by an aging architecture that struggled to handle both live operations and historical queries at scale.
At the same time, the absence of a semantic layer made it difficult to unify diverse data sources and deliver consistent, governed analytics across tenants, while storage costs continued to climb. Together, these issues created bottlenecks in scalability, performance, and cost efficiency—prompting InConcert to partner with Muttdata to design a next-generation, unified data platform on AWS.
The Solution
Muttdata partnered with InConcert to design and deploy a modern, multi-tenant data platform that separates analytics from operational workloads—unlocking real-time, scalable insights for their omnichannel contact center product. Built on AWS, the architecture leverages a message bus (MSK) to decouple data producers from consumers, centralizes access through a governed Data Lakehouse, and powers real-time analytics using StarTree Cloud (Apache Pinot).
Curated data flows from operational systems into the lakehouse and real-time OLAP engine, enabling both batch and streaming use cases without data duplication or pre-aggregation. On top of this, we integrated Cube as a headless semantic layer—allowing internal teams and external SaaS clients to access consistent business metrics via REST and GraphQL APIs. This approach enables personalized data experiences per tenant, supports composite dashboards across products, and accelerates development without increasing engineering overhead.
The entire platform follows a Medallion Architecture, orchestrated via Apache Airflow, and is built for flexibility: engine-agnostic, API-driven, and optimized for future ML and AI use cases. This transformation reduced costs, improved performance, and laid a scalable foundation for InConcert’s next phase of growth.
By combining StarTree’s real-time OLAP engine with Cube’s flexible semantic layer and a robust Lakehouse foundation, InConcert unlocked major performance gains, significant cost savings, and greater agility across its data operations. Report latency dropped from 45 seconds to just 1 second, while storage usage was reduced by 90% thanks to the elimination of pre-aggregated data. Centralizing the platform led to lower maintenance and incident costs, with zero downtime during migration. The system now supports infinite historical retention, offers high availability with regional failover, and enables customers to build tailored reports using curated, real-time data—all while streamlining operations and future-proofing the platform for growth.
