Data & AI Engineering
Building intelligent, governed data ecosystems and next-gen AI capabilities
Data and AI are no longer side projects, they're the foundation for business differentiation. We engineer scalable, compliant, and intelligent data platforms that power advanced analytics, machine learning, and GenAI. From architecture to automation, ENGNX helps organizations build modern, cloud-native data and AI environments that unlock real-time insights, automation, and innovation, securely and at scale.
Modern Data Architecture & Platforms
We architect and implement modern, cloud-native data platforms that form the backbone of AI innovation.
- Data lakehouse and semantic layer design
- Event-driven and real-time data processing
- Data mesh and domain-oriented architectures
- Data governance, lineage, and quality automation
Data Engineering & Integration
We engineer seamless, automated data pipelines that connect your ecosystem and enable governed access to analytics-ready data.
- ELT/ETL orchestration and automation
- Data quality, lineage, and validation pipelines
- Metadata and catalog integration
- Policy-as-code enforcement for compliance
AI & Machine Learning Engineering
We design, build, and deploy AI systems that move beyond experimentation into production-grade impact.
- Bespoke AI agent and GenAI development
- Predictive and prescriptive ML model design
- RAG and vector database implementation
- Responsible AI and model governance frameworks
MLOps & LLMOps (AI Model Lifecycle Management)
We embed automation, governance, and observability into every stage of the ML and GenAI lifecycle.
- ML/LLM pipeline automation
- Model registry, drift monitoring, and retraining
- Policy-based governance for responsible AI
- Continuous delivery and observability for AI systems
Data Governance & AI Strategy
Data and AI success begins with governance. We help organizations design frameworks that ensure compliance, accountability, and measurable outcomes.
- AI governance frameworks (e.g., NIST AI RMF, EU AI Act readiness)
- Data classification and access controls
- Ethical AI and risk management practices
- AI portfolio roadmap and ROI strategy
Our Engagement Process
Data Discovery & Strategy
Assess your data landscape and AI readiness to define business outcomes and compliance frameworks.
Solution Architecture & Governance Frameworks
Design modular data and AI architectures aligned to best-practice frameworks for ethical, explainable, and compliant systems.
Implementation & Automation
Build and integrate pipelines, data platforms, and AI systems using modern cloud-native patterns and ML pipelines.
Continuous Optimization & Trust
Embed observability, quality controls, and MLOps practices to monitor performance, compliance, and ROI.
Domain Expertise
Data Lakes / Lakehouse
Modern data storage solutions using Snowflake, BigQuery, and Databricks for scalable analytics and ML workloads
AI RAG Systems
Retrieval-Augmented Generation platforms that combine vector databases with LLMs for intelligent document processing
AI SaaS Products
End-to-end AI-powered software solutions with multi-tenant architecture, API management, and real-time inference
Real-time Data Pipelines
Event-driven streaming architectures using Kafka, Apache Flink, and cloud-native services for instant data processing
Data Visualization & BI
Interactive dashboards and business intelligence solutions using Tableau, Power BI, and custom web-based analytics platforms
MLOps Platforms
Complete machine learning lifecycle management with model versioning, A/B testing, and automated deployment pipelines