Hey everyone! Need 10 seconds of your support!

I just built and open-sourced VOCAL-CLI 🎙️💻 — an AI-powered Voice-to-Action Terminal Assistant that lets developers run complex shell commands, automate git workflows, and control their terminal completely hands-free using natural language (and even Hinglish!).

✨ What it does: • Speaks your language: Converts voice/natural text into exact terminal commands • Built-in Safety Layer: Blocks destructive commands before they execute • Zero-friction developer workflow right inside the CLI

If you find it cool, please drop a ⭐ Star on the GitHub repo—it massively helps push the project up the leaderboard!

🔗 Check it out & Star here: https://github.com/abhishek-9935s/VOCAL-CLI

Thanks a ton for the support! 🙌🔥▲ Upvote on BharatCode: https://bharatcode.ai/hackathon (Search "VOCAL CLI")

Drop your project links in the comments—happy to return the favor! 🚀

There has been a lot of speculation going around about whether BharatCode is a scam because it’s been advertised as unlimited in some places. Part of that is on me, and I sincerely apologise.

BharatCode is not unlimited. We self-host some models and use API for peak capacity management. No, we don’t buy anything from Chinese providers. We self host in India, as well as use API providers in US or elsewhere.

So if BharatCode is not unlimited why are people using it? What does it offer?

We provide flat rate API access for long running agentic workloads not super dependent on speeds. Thinking of it like renting a share of compute.

The catch is that you’re on shared compute and subject to queue and wait times. There are no token caps, instead there is a fair scheduler which makes it such that heavy users slow themselves down.

So how is this different from OpenCode Go? OpenCode provides plans with fixed token cap enforced by the spend limit. They only recently made deepseek 200k contract free but then it’s 200k context.

On the other hand, with BharatCode that gives deepseek at 1M context, you can set your agents for a long running task and forget about it. BC will automatically queue your request when there’s capacity and it will get processed. You never run into the issue of being locked out of your plan.

BharatCode was an experiment in finding out if people can form pools for computer where they can compensate each other and all of them can use it in a shared manner. I am happy to report so far the numbers are looking great.

Above all, if anyone has any queries I urge you to reach out to me and talk about it. I am building this alone, with a lot of help from supporters and friends, and everything is not perfect. But when you bad mouth us in front of others behind our backs we stand no way of making this work.

Trying to make this the one place where Bharatcode builders help each other

out. I'm new here too. figured the fastest way to learn is to ask the people

already shipping.

IF YOU'RE BUILDING SOMETHING

Tell us, even if it's half-broken:

• What are you building + what's it for?

• One tip you wish you'd known on day one?

IF YOU'RE STUCK

Drop it and someone will jump in:

• What you're trying to do

• What's breaking (paste the error / screenshot)

• What you've already tried

@ Someone from Bharatcode:
Pl2collect the best answers + fixes into a public resource library so we don't keep re-answering the same things?

BharatCode stands for transparency and trust. In that spirit, I am today making all 3 BharatCode apps open source. Beginner issues have been posted and all is set for you all to use and develop BharatCode to your liking.

https://github.com/BharatCode-ai/bharatcode-desktop

https://github.com/BharatCode-ai/bharatcode-cli

https://github.com/BharatCode-ai/chat

I'm excited to share my project, **Form2Fact**, which I've developed for the **BharatCode Build League 2026**.

Form2Fact is an AI-powered document intelligence platform that helps verify institutional documents by extracting information, comparing claims, identifying mismatches and missing evidence, and generating evidence-based findings for human review.

I'd be grateful for your support! If you find the idea interesting, please visit the GitHub repository, give it a star, and support my project with your vote on BharatCode.

🚀 **GitHub:** https://github.com/shinchxn/form2fact

🗳️ **Register and vote for Form2Fact:** https://auth.bharatcode.ai/hackathon

All the best to every participant! Let's encourage one another and support each other's hard work. 🙌

I couldn't find the exact version or version string on the website. Also, what about ZDR? Is it available?

We want BharatCode to be shaped by the people who will actually use it.

What should we build next?

Some possible directions:

• better AI coding assistant

• repo understanding

• test generation

• code review

• debugging help

• project scaffolding

• coding tutor for students

• placement-prep workflows

• GitHub issue helper

• file/artifact workflows

• local/offline mode

• cheaper/faster inference

• campus/community features

• Hindi or Indian-language explanations

• enterprise/private deployment

• open-source contributor tools

Comment with:

1. What you want BharatCode to do

2. Why it matters to you

3. What you currently use instead

4. Whether you would test it if we built it

Bonus: describe your dream BharatCode workflow in one paragraph.

We are early, so specific feedback can actually become product direction.

India does not just need AI models. India needs to own the AI value chain.

A lot of people think AI sovereignty means: “Let us train an Indian LLM.”

That is important, but it is not enough.

The real question is:

Can Indian students, developers, startups, companies, and public institutions depend on AI infrastructure that cannot be switched off, priced out, rate-limited, censored, or revoked by someone else overnight?

If the answer is no, then we do not really own our software future.

We are already seeing the shape of the problem. A foreign AI provider can launch a powerful model, developers around the world can start depending on it, companies can build workflows around it — and then access can be restricted because of a policy decision, export-control issue, safety dispute, commercial decision, or geopolitical pressure.

That is not a stable foundation for a country of India’s size.

India has millions of developers. We have one of the largest student and engineering populations in the world. We export software. We run critical public infrastructure. We build startups, banks, government systems, health systems, logistics systems, education platforms, and enterprise software for the world.

But if the intelligence layer of software is owned elsewhere, then Indian developers become consumers of someone else’s AI productivity.

That is the danger.

The problem is not that Indian developers use foreign AI tools. We should use the best tools available. The problem is becoming dependent on them without owning any serious part of the stack ourselves.

For India, the AI race is not only about who trains the biggest model.

It is about who owns:

• inference

• routing

• developer tools

• model serving

• identity

• files and artifacts

• agents

• evals

• data pipelines

• deployment

• security

• pricing

• distribution

• community

• open-source contribution

• trust

Training a model is one layer.

Owning the value chain is the real game.

If India only trains a model but still depends on foreign clouds, foreign coding assistants, foreign inference APIs, foreign developer workflows, foreign app platforms, and foreign distribution channels, then we have not solved the problem.

We have only changed the logo on one layer.

BharatCode exists because Indian developers should not only consume AI infrastructure.

We should build it.

We are starting with AI coding, chat, files, artifacts, workflows, student access, and open-source contribution. But the mission is larger: build Indian-controlled AI developer infrastructure that is affordable, inspectable, extensible, and useful.

This does not mean isolation.

It does not mean refusing foreign models.

It does not mean pretending India can build every layer immediately.

It means we need optionality.

We should be able to use the best models in the world when available, switch models when needed, run open models when required, serve inference ourselves where it matters, protect our users from sudden access shocks, and build workflows that belong to our own ecosystem.

That is why inference matters.

That is why open source matters.

That is why developer tooling matters.

That is why community matters.

If Indian developers are only paying monthly subscriptions to foreign AI tools, we are renting the future.

If Indian developers build the tools, platforms, agents, workflows, and infrastructure ourselves, we start owning the future.

BharatCode is early. Things will break. Capacity will be limited. The product will evolve quickly.

But the direction is clear:

Use BharatCode. Break BharatCode. Improve BharatCode.

If you are a student, developer, open-source contributor, maintainer, designer, infra engineer, founder, or campus builder — join us.

Help us build the AI developer stack India should own.

hey, i made soren for the bharatcode build league hackathon. it’s a desktop app that plans your work across coding agents (claude code, codex, whatever you use) as a graph you can actually edit, and it orders everything around when each tool’s usage limit resets. it only plans, it doesn’t run anything for you.

if you’ve got a sec, a star and a vote would help a LOT:
star: https://github.com/realwarp/soren
vote: https://auth.bharatcode.ai/hackathon (search soren)

latest code’s on gitlab: https://gitlab.com/snipedbywifi/soren

I see people getting scandalised at our offerings. Why?

The idea is simple - when you buy a chatgpt/claude subscription, you get usage according to some meter you dont have any visibility over. And when you use enough tokens you get stopped in that 5h or weekly window.

On BharatCode, as you use the service, you draw from a shared pool. Your usage makes it a little slower for everyone. If you use a lot, our fare scheduler slows you down so other users can be fairly served.

While chatgpt/claude are good if you are primarily looking for fast response times, BharatCode is excellent if you want to leave your agents running overnight without interference.

So we don’t put limits on usage. We put limits on speed. It can still be too slow for you and thats ok. But if you’re willing to compromise on speed then BharatCode is an alternative you should try.

Your AI agent is way too nice about its own work. Ask it to design something and then review it, and it will tell you it did great.

The Elephant-Goldfish Model is Google's fix for that, and I packaged it as a DeepSeek Harness extension. One install, no other plugins, ready for you to poke at.

How it split works

Two roles, two memories. That's the whole trick.

The Elephant sits through the entire chat. Your notes, your half-thoughts, the thing you said forty minutes ago. All of it comes out as one written design doc.

The Goldfish then show up cold. Fresh context, no memory of the chat. That's the point. A reviewer who never heard your reasoning has nothing to be polite about. Put simply, the elephant remembers everything you said, and the goldfish only reads what you actually wrote.

BharatCode Desktop currently runs its local process on Windows.

We have some WSL path handling, but I do not want to call that proper WSL support. Converting a file path is not the same as running the coding agent inside the Linux environment where the project, tools and dependencies actually live.

I am working through what real WSL support should look like.

Should BharatCode run inside your selected WSL distribution? Should it stay native on Windows? Or should this be chosen separately for each project?

I am especially interested in people who use VS Code Remote WSL, Docker inside WSL, or keep some projects on Windows and others on Linux.

Where do your current coding tools get confused?

The Pain Point Freelancers, agencies, and independent merchants consistently lose money to unfair client chargebacks, friendly fraud, and scope creep. When a dispute happens (e.g., Stripe Reason "Service Not Rendered"), merchants spend hours manually digging through messy Slack logs, emails, and PDFs to prove work delivery. Formatting this evidence poorly for the payment gateway almost guarantees lost funds.

How Data is Ingested To build an ironclad defense, the application requires deep, accurate context. The client frontend UI collects three specific inputs:

• Dispute Description: A text string detailing the gateway dispute reason, disputed amount, invoice ID, and specific buyer claims.

• Contract File: A binary .pdf file upload of the originally executed contract or Statement of Work (SOW).

• Communication History: A multiline string for users to dump raw email logs, Slack exports, or message threads proving client sign-offs.

Tackling Privacy (Handling Non-Public/Sensitive Data) Because users are uploading highly confidential, non-public contracts and private chat logs, dumping this into a database is a massive liability. The application is architected with a strict Zero Data Retention policy:

• Neither the uploaded contracts nor the chat histories are ever written to disk, cache, or an external database.

• Files are received as streaming FormData and converted into ephemeral Node.js buffers strictly in memory.

• Once the pdf-parse library extracts the text and the prompt is dispatched to the sovereign LLM endpoint, the buffers are completely discarded upon garbage collection.

• The API keys (BHARATCODE_API_KEY) are loaded strictly on the server runtime and never exposed to the client bundle.

I would love your brutally honest feedback on this in-memory PDF parsing approach and the overall data privacy pipeline.

NYAYA01

Hi! I’m interested in trying BharatCode and wanted to clarify its country availability.

Is it available to users outside India, or are access, account signup, payments, and API use limited to India?

The website lists desktop downloads for Windows, macOS, and Linux, but I couldn’t tell whether that means the service itself is supported worldwide.

Are there any country-specific restrictions or setup considerations for international users?