Where Enterprise Data Becomes AI at Scale
We help organizations turn enterprise data platforms into scalable, operational AI through strong architecture, governance, and delivery.
Our Services
We design and implement production-grade Retrieval-Augmented Generation (RAG) and LLM platforms that connect trusted enterprise data to modern AI systems.
Our work includes:
End-to-end RAG pipelines covering document ingestion, parsing, chunking, embedding generation, vector indexing, retrieval, and response orchestration
Integration of enterprise data sources into AI workflows with controlled context selection and metadata-aware retrieval
Centralized LLM services supporting governed access, reusable embeddings, routing, and safe-response patterns
Evaluation, observability, and monitoring to support tuning, reliability, and long-term operation
These platforms are built to operate at scale, support multiple teams, and meet enterprise requirements around governance, auditability, and cost control.
We help organizations modernize legacy data platforms into scalable, cloud-native architectures that support analytics, machine learning, and AI workloads.
Our work includes:
Design and implementation of data pipelines for batch and real-time ingestion
Data lake and lakehouse architectures using cloud object storage and analytical engines
Data modeling, schema evolution, and downstream consumption patterns for APIs, analytics, and ML
Performance optimization and cost management for large-scale data processing
These foundations enable reliable downstream use cases, from reporting and analytics to advanced AI and RAG systems.
We design secure, cost-optimized cloud architectures on AWS to support data, analytics, and AI platforms in enterprise environments.
Our work includes:
Architecture and delivery of serverless and managed cloud solutions
Secure API-driven data access and platform integration
Scalable NoSQL and relational data stores for operational and analytical workloads
Real-time data processing using event-driven and streaming patterns
Infrastructure automation and deployment pipelines to support repeatable, multi-environment delivery
All architectures are designed with an emphasis on operational reliability, security, governance, and long-term maintainability.
How We Engage
Our engagements are typically architecture led and delivery-focused. We work closely with client engineering, data, and platform teams to design solutions that can be implemented, operated, and extended over time.
We focus on:
Clear architectural direction
Practical implementation
Knowledge transfer and long-term sustainability
About JadeTech Inc.
Founded in 2005, Jade Tech is an experienced consulting partner specializing in data platforms, cloud architecture, and AI-enabled systems. For nearly two decades, we have helped organizations design and implement data-driven solutions that support analytics, decision-making, and operational systems at enterprise scale.
Our work is grounded in strong data foundations. We design and build data pipelines, data lakes, analytical stores, and APIs that enable reliable downstream consumption—whether for business intelligence, machine learning, or modern AI and RAG platforms. We are deeply experienced across both serverless and managed cloud architectures, with a focus on performance, cost efficiency, governance, and long-term maintainability.
Today, Jade Tech helps organizations evolve these data platforms into scalable, operational AI—connecting trusted enterprise data to modern AI and LLM-based systems through strong architecture, governance, and delivery.
Contact Us
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