Data, AI & Distributed Systems focuses on building data platforms, AI-enabled capabilities, and distributed systems that operate reliably at real-world scale.
Ziverge moves organizations beyond prototypes, delivering systems where data processing, machine learning, and distributed execution are integrated, observable, and resilient in production.
Pipelines are brittle, slow, or inconsistent. Analytics lag behind reality, and teams lack confidence in the data they rely on.
Models work in notebooks but fail in production. Deployment, monitoring, and scaling remain unsolved.
Throughput, latency, or concurrency issues emerge as usage grows, and incremental fixes no longer hold.
We begin with assessment of data pipelines, system architecture, and operational constraints, integrating with existing teams and roadmaps rather than creating parallel efforts.
Data and AI are treated as engineering systems. Pipelines, models, and services are designed together, with observability, deployment, and failure handling considered from the start.
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Most AI consultancies lack distributed systems depth, and most systems teams lack AI delivery experience. Ziverge combines both, building AI-enabled systems that scale because we understand event-driven architecture, concurrency, and fault tolerance.
We design batch and real-time pipelines with strong data quality, governance, and lineage, supporting analytics, operations, and machine learning from a shared foundation.
We deliver end-to-end AI systems, from model development to production deployment and monitoring, with MLOps practices built in.
Our teams build high-throughput, fault-tolerant distributed systems using event-driven and actor-based concurrency patterns proven at scale. In environments where correctness under concurrency is critical, our engineers bring experience applying functional and type-driven design techniques in production systems.
We operate across AWS, Azure, GCP, hybrid, and on-prem environments, using streaming platforms and cloud-native deployment as tools to support reliability and performance.
Ziverge engineers have built systems processing hundreds of thousands of events per second, supporting terabytes of data daily, and operating with uptime exceeding ninety-nine point nine nine percent in mission-critical environments.
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Data pipelines are trusted, AI models run reliably in production, and distributed systems scale predictably as demand grows. Teams gain real-time insight, failures are handled gracefully, and new capabilities can be built with confidence.
Talk to a solutions architect to discuss your data challenges, AI goals, and scaling constraints. We will help you evaluate options and outline a practical path to production-ready data and AI systems.