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@inboxpraveen

Praveen Kumar

inboxpraveen
Bengaluru, India

Hi, I'm Praveen. I'm a Principal AI Engineer in Bengaluru, and I build tools around the problems I run into at work.

Three projects I'm working on:

  • CleanFrame turns a messy spreadsheet into a saved cleaning recipe. You can replay it without making another model call.
  • ThinkLess lets rules and small models handle routine agent decisions, with an LLM for the cases they cannot settle. It is still pre-1.0.
  • MoM AI turns recordings into transcripts, decisions and action items, using local models or providers you choose.

Sponsorship helps me spend more time on fixes, documentation, compatibility checks and experiments that other people can reproduce. If one of these tools saves you time, supporting its upkeep makes a difference.

For company acknowledgements and CleanFrame support, see the tier descriptions. You do not need to sponsor me to use the core features of these projects.

You can find the rest of my projects and research notes on my website. For bugs or contributions, please start with an issue in the relevant repository.

1 sponsor has funded inboxpraveen’s work.

@inboxpraveen

Helps cover development tools, compute for public experiments, and time for fixes and documentation across my projects.

Private Sponsor

Featured work

  1. inboxpraveen/Cleanframe

    The reproducible data-cleaning engine for Python. Profile messy CSVs, detect issues, generate a YAML recipe (with or without an LLM), and replay it with zero AI calls.

    Python 5
  2. inboxpraveen/ThinkLess

    Stop using an LLM for every decision. ThinkLess learns your AI agent's routine LLM decisions and answers them locally once proven, with one line under the OpenAI or Anthropic client. Or run typed d…

    HTML 3
  3. inboxpraveen/LLM-Minutes-of-Meeting

    Turn audio and video recordings into transcripts, decisions and action items. Supports local models, cloud providers and background jobs you can retry.

    Python 175

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$5 a month

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Thanks for backing my work. Your name goes in the sponsors list of the project you sponsor for.

$25 a month

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Your name and a link in the README of the project you sponsor for. Issues you open there get looked at first.

$100 a month

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CleanFrame retainer, patch on demand.
For one recurring file, like a monthly vendor export, a marketplace settlement report, or a CRM dump.

I build the CleanFrame recipe for it. You own it and keep it in your git.
You run it yourself each month.
When the file format changes (a renamed column, a new date format, a new currency layout), I patch the recipe within 3 business days.

$150 a month

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Company sponsor.

Your product gets a short section near the top of the README of the project you choose (LLM Minutes of Meeting or CleanFrame), with your logo, a link, and two or three lines you write. You also get a mention in the release notes of that project. Cancel anytime.

$200 a month

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CleanFrame retainer, monthly run.

Everything in the patch on demand tier, plus:
I run the recipe on each new file and send you the cleaned output with a cell-level diff.
3-business-day turnaround when the format changes.
One custom detector per quarter for your file's specific quirks.

Your data stays on my machine, is never shared or used for training, and is deleted after 30 days.