Data Engineering & Applied AI
Architecting scalable data platforms and deploying production-grade AI solutions. We bridge the gap between raw data and measurable business intelligence.
Core Capabilities
From Infrastructure to Intelligence
Modern Data Platforms
Design and implementation of scalable data lakes, lakehouses, and warehouses on Databricks, Snowflake, and cloud-native services.
Generative AI Integration
Custom LLM fine-tuning, RAG architecture implementation, and semantic search capabilities for enterprise data.
Data Pipelines & ETL/ELT
Robust, fault-tolerant streaming and batch data pipelines using Apache Kafka, Airflow, and Spark.
Reference Architecture
Enterprise RAG Pipeline
Our standard reference architecture for integrating enterprise knowledge bases with Large Language Models securely and efficiently.
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1Data Ingestion via Azure Data Factory / AWS Glue
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2Vector Embeddings generated using OpenAI / Cohere models
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3Storage in Pinecone / Azure AI Search vector databases
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4Semantic Retrieval & LLM Generation Orchestration via LangChain
The Enterprise AI Lifecycle
We don't just build models; we build production-grade AI platforms.
Ingestion
Scalable data pipelines using Spark and Flink.
Refinement
Automated cleaning and feature engineering.
Inference
Low-latency model serving with RAG integration.
Monitoring
Drift detection and automated retraining.
Modern Data Mesh Blueprint
We decentralize data ownership, enabling individual business domains to manage and serve their own data as a product. This architecture eliminates the central bottleneck and accelerates time-to-insight.
- Self-serve data infrastructure
- Federated computational governance
- Interoperable data domains
Ready to Unlock Your Data's Potential?
Schedule a Data & AI strategy workshop with our experts.
Ready to Architect Your Future State?
Join the global enterprises who bypass legacy constraints with OPENZIX Engineering. Schedule a technical review with our principal architects.