Currently building document and voice AI for enterprise teams

Praveen Kumar

Principal AI Engineer & Solution Architect

Six years of it. Mostly speech AI

I take AI systems from the first rough prototype to the version that survives real traffic, real documents and real users. Everything I learn on the way ends up here, written down properly.

See the work About Resume GitHub

Selected work

Three I'd show you first

Fifteen projects live in the archive. These three are the ones that taught me the most about shipping things other people depend on.

LLM & RAG Python pandas PyPI

CleanFrame

A data-cleaning engine you can actually put in a pipeline. An LLM writes the plan once; the plan compiles to a YAML recipe that replays over next month's file in pure pandas — no API calls, same answer every time. When the schema drifts it stops and tells you, instead of quietly corrupting the column.

On PyPI as cleanframe-engine Apache-2.0 Runs fully offline Read the write-up

MoM AI meeting minutes application homepage

LLM & RAG Flask Celery Redis Docker

MoM AI — Minutes of Meeting

Drop in a recording, get back minutes. FFmpeg normalizes the audio, a Celery worker routes it to one of four speech-to-text providers, and an LLM returns the summary, the decisions and the action items. Both providers swap at runtime.

4 STT providers behind one factory Open source Read the write-up

Learning Resource Vanilla JS HTML CSS

Py Internals

An interactive course that teaches Python by drawing its memory. Code on the left, stack and heap on the right, one idea per animation step. No backend, no build step, no account — hand-authored snapshots rendered by a few hundred lines of vanilla JS.

5 sessions, ~23 interactive labs Open source Read the write-up

Browse all 15 projects

The short version

Models are the easy part

The hard part is everything around them: the queue that retries, the tenant boundary that holds, the GPU bill that doesn't spiral, the transcript a human can actually correct. That's the work I've spent six years getting good at — speech intelligence, document processing and LLM automation, mostly for enterprise teams who need it to hold up on a Monday morning.

Years building AI systems

10+

Production AI platforms

50+

Models deployed

Projects written up here

The longer version

Say hello

Got something hard to build?

I like problems where the obvious approach doesn't work yet. Email is fastest, but any of these reach me.

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