Zyvoxal builds streaming, big data, cloud integration, and AI-powered platforms for modern enterprises — from architecture to production.
Every system we build treats latency as a first-class concern — milliseconds matter at enterprise scale.
Designed to grow from thousands to billions of events without re-architecture or downtime.
Embedded ML and anomaly detection that learns from your data patterns automatically.
SOC2 Type II, 99.997% uptime SLAs, and battle-tested in fintech and critical infrastructure.
End-to-end data engineering capabilities — from stream ingestion to AI-powered monitoring.
Apache Kafka, Flink, and Spark Streaming architectures that handle millions of events per second with sub-10ms end-to-end latency.
Learn More →Petabyte-scale data pipelines on Databricks, Snowflake, and Delta Lake — with automated data quality and governance built in.
Learn More →Embedded ML models that continuously monitor your data streams and surface anomalies, degradations, and business risks in real time.
Learn More →Migrate legacy systems to AWS, GCP, or Azure data platforms. We handle architecture, migration strategy, and post-launch optimization.
Learn More →A proven engineering methodology that takes you from discovery to a production-grade data platform.
Deep-dive into your data sources, bottlenecks, and business objectives. Architecture review included.
Design a scalable, cloud-native blueprint tailored to your stack, team, and growth trajectory.
Iterative engineering sprints with embedded QA, observability, and documentation from day one.
Continuous performance tuning, cost optimization, and SRE support after go-live.
From high-frequency trading to IoT fleets — we understand the data challenges of your sector.
Real-time fraud detection, trading analytics, regulatory reporting, and payment processing at scale.
Personalization engines, inventory optimization, clickstream analytics, and demand forecasting.
Fleet tracking, route optimization, predictive maintenance, and end-to-end supply chain visibility.
Usage telemetry, billing event streams, customer success signals, and product analytics infrastructure.
Legacy modernization, data mesh architecture, observability platforms, and cloud migration programs.
Device telemetry ingestion, edge processing, anomaly detection at the device layer, and OTA management.
Battle-tested tools and frameworks — not just certifications, but real production experience.
Apache Kafka, Confluent Cloud, AWS MSK — billions of messages daily.
PySpark, Databricks, EMR — petabyte-scale ETL and ELT workflows.
Custom ML models, Prophet, Isolation Forest, and LLM-enhanced alerts.
AWS, GCP, Azure — Terraform IaC, Kubernetes, serverless architectures.
gRPC, REST, GraphQL, and async event-driven microservice architectures.
OpenTelemetry, Prometheus, Grafana, Datadog — full-stack visibility.
A production-grade, cloud-native data platform architecture — from raw events to executive dashboards.
Not consultants with slides — engineers who've shipped production data systems at scale.
Our team includes ex-Google, ex-Databricks, and ex-Confluent engineers who built the tools you rely on. We write code, not decks.
240+ enterprise deployments across fintech, e-commerce, and logistics. We've seen every failure mode — and engineered around it.
We embed ML where it creates real value: anomaly detection, demand forecasting, and intelligent alerting — not AI for its own sake.
Architecture decisions today that won't become your technical debt tomorrow. We design for 10x, 100x, 1000x scale from the start.
We don't recommend tools we don't run ourselves. Our reference architecture evolves with the ecosystem — not behind it.
We don't disappear after go-live. Embedded SRE, on-call support, and quarterly architecture reviews are part of our engagement model.
"Zyvoxal reduced our fraud detection latency from 800ms to under 12ms. The Kafka + Flink architecture they designed handles our peak trading volume without a single dropped event."
"The data platform migration was delivered on time, under budget, and with zero production incidents. Our data team was skeptical — now they can't imagine working without it."
"Their AI anomaly detection caught a supply chain disruption 6 hours before our operations team would have noticed it manually. That single detection saved us $2.4M."
Real outcomes from real engagements — numbers our clients approved.
Rebuilt NexPay's fraud pipeline on Kafka + Flink. From 800ms batch scoring to sub-12ms stream detection.
Built a real-time recommendation system processing 40M user events/day — serving 200ms personalized product feeds.
End-to-end IoT telemetry ingestion from 12,000 fleet assets. Real-time ETA prediction and anomaly alerting.
Practical guides and deep-dives from our engineering team.
How we designed a 48-partition topic topology that handles 500K transactions/sec without rebalancing storms.
Step-by-step guide to deploying a real-time anomaly detector on Flink with custom ML model serving.
Spot instance strategies, cluster autoscaling, and Delta Lake compaction patterns that saved one client $540K/year.
Tell us about your data challenge. We'll respond within one business day with a tailored perspective — no sales pitch required.
30-minute architecture review session. We'll come prepared with observations about your stack.
Share your current architecture and we'll return a written assessment with improvement recommendations.
Direct access to a senior data engineer — not an SDR. Real technical conversations from the first call.
Join 240+ enterprises running production-grade real-time data platforms on Zyvoxal-built infrastructure.