Focused  ·  Production-Grade  ·  Value-First

Engineering Data & AI
that ships.

A small, expert team building data pipelines, cloud infrastructure, and agentic AI systems — delivered at a pace and price that makes sense for your team.

Data Engineering Cloud Architecture Agentic RAG Java · Python · Go
Data analytics and AI — transforming fragmented data into actionable intelligence
The Challenge Today

Most organisations capture vast amounts of data — yet only a fraction is ever structured, connected, or analysed. AI-powered pipelines bridge that gap, turning scattered signals into clear decisions.

80%of enterprise data goes unanalysed
productivity with AI data pipelines
↓40%decision latency with unified data

Our Expertise

From raw data ingestion to autonomous AI agents — we cover the full engineering stack.

⚙️

Data Engineering

Robust ETL/ELT pipelines, data lakes, and warehouses architected to scale reliably with your business needs.

  • Apache Spark
  • Airflow
  • dbt
  • Kafka
☁️

Cloud Architecture

Resilient, cost-efficient cloud infrastructure across AWS, Azure, and GCP — designed for security and scale.

  • AWS
  • Azure
  • GCP
  • Terraform
🔗

Pipeline Building

End-to-end data and ML pipelines with monitoring, alerting, and automated recovery baked in from the start.

  • MLflow
  • Prefect
  • Dagster
  • CI/CD
🤖

AI Integration

Embedding LLMs and AI capabilities directly into your systems — APIs, workflows, and user interfaces.

  • OpenAI
  • Anthropic
  • LangChain
  • Bedrock
🧠

Agentic RAG Models

Autonomous retrieval-augmented agents that reason over your domain data, retrieve context, and take action.

  • LlamaIndex
  • Pinecone
  • Weaviate
  • Agent Loops
📊

Analytics & Insights

Turning complex datasets into clear dashboards and decision-ready insights your team can act on immediately.

  • dbt
  • Tableau
  • Power BI
  • Looker
🛠️

Code Modernisation

Rewriting, refactoring, and enhancing legacy codebases in Java, Python, and Go — cleaner architecture, better performance, lower maintenance burden.

  • Java
  • Python
  • Go
  • Refactoring
  • API Design

Real Challenges, Real Outcomes

From rescuing legacy systems to shipping production AI pipelines — here are problems we have tackled for real clients.

Data Migration

Legacy Data to SaaS Platform

Challenge15 years of siloed data across on-premise Oracle databases and flat files, blocking a move to a modern SaaS CRM.

OutcomePhased ETL migration to Snowflake + Salesforce Data Cloud in 10 weeks — zero downtime, full historical data preserved.

  • Python
  • Snowflake
  • dbt
  • Airflow
Cloud Analytics

On-Premise BI to Cloud Analytics

ChallengeSlow, expensive Tableau reports running off an aging on-prem SQL Server — insights were days late and IT was overwhelmed.

OutcomeMigrated to GCP BigQuery with a streaming ingestion layer. Dashboards refresh near real-time; infra costs dropped 45%.

  • GCP
  • BigQuery
  • dbt
  • Looker
Agentic AI

RAG Pipeline for Enterprise Knowledge

ChallengeEmployees needed to query thousands of internal policy documents without a dedicated search team or expensive enterprise search licence.

OutcomeBuilt an agentic RAG system on AWS Bedrock — employees ask in plain English, the agent retrieves, reasons, and responds with cited sources in under 3 seconds.

  • AWS Bedrock
  • LlamaIndex
  • Pinecone
  • Python

Pipeline Blueprints

A transparent look at how our data engineering and agentic AI pipelines are structured end-to-end.

Data Engineering Batch + Streaming Pipeline
💾
Sources
S3 · Postgres · APIs
Ingest
Kafka · Fivetran
⚙️
Transform
Spark · dbt
🗄
Store
Snowflake · BigQuery
📈
Serve
APIs · BI · dbt
Agentic AI RAG + Agent Loop
💬
User Query
Natural language
🔍
Retrieve
Vector search
📄
Context Build
Re-rank · chunk
🧠
LLM Agent
Claude · GPT-4o
🚀
Output
Answer + sources

Try Our Work Once

Trust is earned through results, not proposals. We offer a focused pilot engagement — real deliverables, clear scope, honest pricing. Good outcomes at budgets that make sense for your team size.

Start a Pilot  →
🎯

Scoped & Bounded

Fixed scope, clear deliverables, 2–4 week sprints. No creep, no surprises.

💰

Smart Value

Enterprise-quality engineering without enterprise-agency overhead — scoped precisely to what you need.

Real Deliverables

Working code, deployed pipelines, or a live demo — not just a slide deck.

A Small, Expert Team

A tight-knit group of engineers who move fast, build clean, and deliver real outcomes — without the overhead of a large agency.

🎯

Deep Focus

We specialise sharply rather than spreading thin — every project gets our complete attention.

Agile & Fast

Small team means fast iterations, direct communication, and zero bureaucratic overhead.

🔮

Research-Driven

We stay at the cutting edge — from the latest LLM releases to emerging cloud paradigms.

🤝

Collaborative

We work closely with your team, not around it — full transparency from day one.

Watch It in Action

Curious about what we build? We will walk you through a live demo — no sales pitch, just real engineering.

agentic-rag · pipeline-run

$ run-pipeline --config prod.yaml --agent rag-v2

✔  Loading vector store  (Pinecone · 2.4M vectors)

✔  Connecting data sources  (S3, Snowflake, Postgres)

✔  Initialising RAG agent  (Claude 3 · 200k context)

✔  Orchestrating pipeline  (Airflow · 12 tasks)

What You Will See

  • A live data pipeline ingesting and transforming real data
  • An agentic RAG model answering questions over your domain
  • Cloud architecture walkthrough — infrastructure as code
  • AI integration connecting LLMs to your existing systems
Request a Demo  →

Get in Touch

Interested in working with us or seeing a live demo? Drop us a message and we will get back to you within 24 hours.

✉️

Email Us

datainfscale@gmail.com

🌍

Availability

Remote · Worldwide