Data Engineering · Analytics · AI

DataPipelinesThat Survive Contact With Production

We engineer streaming ingestion, cloud data platforms, and AI agents for enterprise systems — built on real production experience with zero corporate fluff.

Capabilities & Services

How we can help you scale

Choose the path that fits your current operational and technical needs

data

Data Platforms & Pipelines

Transform raw event streams and database mutations into secure, governed cloud data platforms.

  • Data warehouse architecture for scalable analytics & CDC
  • Centralized metrics governance & single source of truth
  • Compute cost optimization — slash cloud database bills
  • Automated incremental data pipelines & real-time ingestion
ai

AI Agents & Analytics Interfaces

Connect enterprise schemas to AI agents and natural language query systems.

  • Secure natural-language interfaces for internal databases
  • Autonomous workflow agents for operational processing
  • Vector search & RAG across structured and unstructured data
  • Enterprise LLM integration without private data leakage
training

Training & Engineering Talent

Upskill engineering teams or source pre-vetted data practitioners.

  • Production-grade data engineering training & mentorship
  • Vetted data talent placement for enterprise engineering teams
  • Modern analytics engineering & dbt model governance
  • Secondary capabilities: custom internal tools & portal interfaces
Data & AI Solutions

Architectures built for production

We design, build, and optimize enterprise data platforms, AI-powered automation, and operational analytical portals.

01 / Design & Build

Custom Software & Data Portals

We build internal data portals, executive dashboards, and operational web tools engineered directly over modern data architectures.

  • Operational web applications tailored to business data workflows
  • Client portals and internal dashboards linked to analytical databases
  • High-performance UI/UX design with responsive data visualizations
  • Custom API integrations and automated data management interfaces
Next.js & ReactData PortalsInteractive UIAPI Connectors
client_portal_v2.app
Active

Volume

5M+ CDC

SLA Reliability

99.9%

Cost Saved

~60%

02 / Audit & Architect

Cloud Data Platforms & Analytics

We turn messy, scattered data sources into a single source of truth—slashing cloud costs, automating reporting, and delivering clear business insights.

  • Connect database silos into a centralized, modern warehouse
  • Unify KPIs so your finance, sales, and product teams trust the same numbers
  • Identify and eliminate unnecessary database queries to cut cloud bills
  • Automate routine data updates so dashboards are always fresh
Cloud WarehouseData PipelinesData GovernanceCost Optimization
Read our data engineering approach
data_pipeline_ingest.sync
Processed: 5M+ CDC records/day
APILogsDBWarehouse
03 / Model & Integrate

AI Agents & Cognitive Automation

We connect your database schema to AI agents and natural language interfaces, letting your team query insights in plain English and automate complex back-office chores.

  • Securely query enterprise records using natural language search
  • Build cognitive workflow agents to autonomously process incoming tasks
  • Uncover hidden knowledge across scattered sheets, docs, and PDFs
  • Integrate LLMs securely without exposing private customer data
AI AgentsNatural QueryingMCP ServersIntelligent Workflows
agent_agentic_mcp.sh
Agent Active
User:Analyze Q2 sales conversions & recommend actions.
Our Methodology

How we partner with you

A structured, practitioner-led engineering process built for reliability and maintainability

Week 1

1. Source-System Audit

We evaluate your source databases, schemas, record volume, and exact freshness requirements before designing any pipelines.

Week 2

2. Architecture & Strategy

We define batch vs streaming boundaries, compute cost limits, and SLA targets to construct a maintainable system design.

Week 3-6

3. Production Build

We build versioned transformation models, CDC triggers, or AI agent interfaces with automated monitoring and retries.

Week 7-8

4. Handover & Governance

We transfer complete infrastructure modules, document data contracts, and train your internal engineering team.

Work & Insights

Case Studies & Publications

Explore our real-world client implementations, architectural audits, and advanced engineering articles.

Case Study5M/day CDC Records Processed in 1h Batches

SAP ECC to Databricks Lakehouse: Enterprise CDC Architecture on Azure

Architected an enterprise Lakehouse solution migrating 5M daily CDC records from SAP ECC (Oracle) to Azure Databricks. Features ODP/OData ingestion, automated PySpark schema evolution & drift alerting, multi-tier data quality quarantine, and Serverless compute optimization.

SparkPythonSQL
Case Study50–100 Agent Runs / Day

Natural Language Data Agent

A domain-agnostic AI agent that lets analysts query data, helps engineers trace pipelines, and gives engineering managers visibility into team work from plain-English questions.

Enterprise LLMsRAGVector DBLooker
Case Study10-100 Daily Self-Serve Queries

AI-Powered Analytics Assistant

Built a conversational analytics assistant that converts natural language into cloud SQL, enabling business users to self-serve repeated data pulls in real time.

Enterprise LLMsRAGPythonSQL
Insight20-30% Velocity Boost

Multi-Agent Development Framework

Designed an advanced multi-agent development workflow and orchestration framework, improving development speed and consistency across design, build, test, and documentation.

Agent FrameworkMulti-AgentMCPProductivityOrchestration
Get In Touch

Ready to build scalable data platforms or deploy AI agents?

Tell us your source systems, volume, and latency requirements. Book an engineering consultation or send a message, and we'll reply within one business day.

Faridabad, India & Remote
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