TechBatonData Analytics & AI Engineering
Secure, production-ready AI pipelines and advanced data architectures that turn complex enterprise telemetry and operational data into accessible insights.
The problem
Organizations want to leverage AI and advanced analytics to query their enterprise data but face significant structural and security roadblocks. Traditional ERP reporting requires rigid Business Intelligence tools and SQL engineers, preventing business users from getting immediate answers to everyday questions. Furthermore, fragmented operational datasets, complex telemetry logs, and unrefined ETL processes make it difficult to establish a single source of truth.
Conversely, hooking a Large Language Model (LLM) directly to a live financial database risks AI hallucinations, inaccurate metrics, and severe security vulnerabilities like unauthorized data mutation. Leadership is rightfully hesitant to expose sensitive financial ecosystems to unpredictable AI agents without strict governance.
Our approach
We build secure, boundary-aware AI systems and scalable data pipelines that act as intelligent translators between your business users and your enterprise data. Instead of allowing AI to write raw SQL directly to your database, we implement robust architecture patterns that serve as a read-only execution firewall.
We focus on rapid velocity through hybrid data strategies. By seamlessly connecting your live staging tables with strategic mock schemas, we can bridge data gaps and prove business value in agile sprints before requiring heavy, permanent data migrations.
Tech stack examples
Data Integration & ETL
Develop scalable data pipelines to extract and transform data from multiple enterprise sources, APIs, and operational datasets.
Telemetry & Log Analysis
Leverage Azure Data Explorer (Kusto) and KQL to analyze complex telemetry systems, extracting trend analysis and risk metrics.
Semantic Modeling
Design robust semantic models and analytics solutions that support engineering, security, and business stakeholders.
Business Intelligence
Design and maintain executive dashboards and operational scorecards using Power BI and Microsoft Fabric technologies.
Agentic AI Orchestration
Utilize multi-step reasoning and semantic intent parsing using models like Anthropic Claude via AWS Bedrock or Google Vertex AI.
Secure Middleware
Deploy custom Model Context Protocol (MCP) servers on cloud containers to handle automated schema discovery and secure, read-only tool execution.
Conversational Interfaces
Build chat-driven data portals equipped with interactive data grids, line-item drill-downs, and instant Excel/PDF document serialization.
Case example
For a large enterprise client running a heavily customized, multi-module ERP system, we built an AI-powered Accounts Payable (AP) reporting module. The objective was to enable finance and procurement users to ask conversational questions and receive instant, structured financial reports without needing to know SQL.
Delivered as a high-velocity 2-week Proof of Concept (POC), we designed a cloud-native Agentic AI framework. Instead of allowing open SQL execution, we deployed a custom Model Context Protocol (MCP) Server as a secure middleware. To overcome missing invoice allocation logic in the live database, we employed a hybrid data strategy, connecting live operational tables with a single mock bridge table to accurately compute invoice aging. The resulting application allowed executives to view interactive data grids with one-click exports, all while maintaining absolute data perimeter security.