Korba, Chhattisgarh

AI Integration & AI Product Development in Korba.

RAG pipelines and autonomous LLM workflows built into your product. Mojo Studio delivers ai products for founders and businesses in Korba, senior engineers only, weekly demos, full IP ownership.

How we build it

Built right,
shipped fast.

We integrate production-grade AI into real products — custom RAG pipelines over your own data, autonomous LLM agent workflows, and semantic search, built with the same engineering rigor as the rest of your stack. This isn't a chatbot bolted onto a landing page; it's AI wired into your actual product logic, with the guardrails to keep it from hallucinating in front of customers.

Custom RAG pipelines over your own data
LangChain / LangGraph agent workflows
Semantic search & vector database integration
Guardrails against hallucination in production
Local context

Built for Korba's market.

Korba is Chhattisgarh's energy capital — South Eastern Coalfields Limited (SECL) runs major mining operations here, feeding one of India's largest clusters of thermal power stations (including NTPC Korba) alongside Balco's (Bharat Aluminium Company, part of Vedanta) large aluminum smelting complex. That combination of coal, power, and heavy metals makes the local economy almost entirely industrial-B2B: equipment suppliers, mining contractors, and power-plant service vendors dominate, with very little consumer-facing commerce. Digital demand is narrow but real — mainly procurement, safety-compliance, and logistics tooling for large industrial operators and their contractor networks.

Korba's coal mining (secl) and thermal power generation (ntpc) businesses have specific needs when it comes to ai products — this is the local context that shapes how we scope every Korba engagement, not a generic playbook applied everywhere.

Coal mining (SECL)Thermal power generation (NTPC)Aluminum smelting (Balco/Vedanta)Industrial contracting
Our Process

From brief to launch.

01

Use-case scoping — where AI actually adds value vs. hype

02

Data pipeline & vector store architecture

03

Model integration (OpenAI, Gemini, Claude, or fine-tuned)

04

Evaluation, guardrails, and production monitoring

Common Questions

AI Products FAQ.

Grounded retrieval (RAG) over your actual data, tight prompt scoping, output validation layers, and explicit fallback behavior when the model isn't confident — hallucination is a design problem, not something you patch after launch.

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