ABOUT TASPRA
Built by an engineer.
Designed to last.
TASPRA is an AI technology studio — one person, a clear philosophy, and a track record of building systems that work in production, not just in demos.
THE PERSON
Hi, I’m AION.
I’m a data and AI engineer with a background in telecom-scale infrastructure — pipelines handling billions of events, systems that can’t afford to fail at 3am, and data that actually has to be right.
I started TASPRA because I kept seeing the same gap: teams with hard problems and AI that looked impressive in a pitch but fell apart in production. I build the other kind.
Based in India. Working with teams globally — particularly in the Gulf region, where a lot of the data and AI infrastructure work I care about is happening.
PRIMARY EXPERTISE
Data Engineering · AI Systems · Automation
CORE STACK
Python · PySpark · Delta Lake · SQL · LLMs · RAG · Kafka · REST APIs · WordPress + WooCommerce
DOMAIN EXPERIENCE
Telecom · Financial Planning · Data Platform Engineering · NRI Finance · Digital Products
PHILOSOPHY
How TASPRA thinks about building.
Production over demos
Impressive demos aren’t the goal. Systems that still work reliably six months later — that’s the standard. Every project is built for the failure cases, not just the happy path.
Specific, not general
AI is a tool, not a category. Every system built here solves a specific, named problem — not “we’re adding AI to everything.” If the problem isn’t worth solving, the project doesn’t start.
Honest about limits
No invented metrics, no fake case studies, no credibility manufactured from thin air. What’s live is marked live. What’s in progress is marked in progress. That’s it.
Speed with structure
Moving fast doesn’t mean skipping the architecture. The goal is systems that are fast to build and fast to change — not systems that need a full rewrite the moment requirements shift.
Global problems, real impact
The work focuses on problems that matter to real people — NRIs navigating complex financial systems, teams drowning in data they can’t use, businesses losing customers they could have kept.
Build in public
The process is documented — not just polished outcomes. Build Notes shows what was built, how, and what didn’t work the first time. Because that’s how people actually learn.
ENGINEERING JOURNEY
Where the experience comes from.
Years of building at scale — not side projects, but systems that process millions of records daily in live production environments.
DATA ENGINEERING
Telecom-scale data pipelines
Designed and built PySpark-based data pipelines processing Call Detail Records at telecom scale. Rebuilt legacy batch systems into lakehouse architectures using Delta Lake — systems that handle schema evolution without emergency patches.
MACHINE LEARNING
Production ML, not notebook ML
Built churn prediction models that plug directly into retention campaign systems — not reports, but automated pipelines that generate daily ranked lists of at-risk customers and feed them into CRM tooling.
AI ENGINEERING
LLMs with guardrails
Working with LLMs, RAG systems, and AI agents in contexts where hallucination is not acceptable — billing data, financial documents, operational systems. Building the grounding, evaluation, and fallback logic that makes AI reliable rather than just impressive.
PRODUCTS & STUDIO
TASPRA — building in public
Founded TASPRA to package engineering expertise into products, services, and digital resources — starting with the NRI Financial Toolkit for the Gulf NRI community, and a growing catalog of AI and data engineering tools.
STACK & TOOLS
What gets used to build things.
Not a buzzword list — the actual tools in active use across live projects.
Python
Core language
PySpark
Distributed data
Delta Lake
Lakehouse storage
LLMs / RAG
AI reasoning
SQL
Data querying
Kafka
Streaming
REST APIs
Integration
WooCommerce
Digital storefront
WHAT TASPRA IS FOR
The right fit for the right problems.
TASPRA works best with teams that have real data problems, a tolerance for honest assessments, and the patience to build things properly — not teams looking for a quick AI integration to put in a deck.
GOOD FIT ✓
- You have a messy data problem with scale
- You want AI that actually works in production
- You need automation that reduces real hours
- You’re building something new and need an engineering partner
- You want honest tradeoffs, not just “yes”
NOT A FIT ✗
- You want AI for the press release, not the product
- You need a yes-person, not a collaborator
- You’re looking for the cheapest option
- You need a large agency with 20 people on the call
- You want something built in a day