Bokaro, Jharkhand

AI Integration & AI Product Development in Bokaro.

RAG pipelines and autonomous LLM workflows built into your product. Mojo Studio delivers ai products for founders and businesses in Bokaro, 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 Bokaro's market.

Bokaro Steel City was built in the 1960s around Bokaro Steel Plant, developed with Soviet collaboration as one of India's five original public-sector integrated steel plants (alongside Bhilai, Durgapur, and Rourkela), and it remains a tightly planned SAIL township rather than an organically grown commercial center. The local economy runs almost entirely on the steel plant and its ancillary vendor base, with limited independent commercial or startup activity outside that ecosystem. Digital demand here is concentrated in vendor-management, procurement, and logistics tooling for steel-linked suppliers rather than consumer-facing products.

Bokaro's integrated steel manufacturing (sail/bokaro steel plant) and industrial ancillary & vendor supply businesses have specific needs when it comes to ai products — this is the local context that shapes how we scope every Bokaro engagement, not a generic playbook applied everywhere.

Integrated steel manufacturing (SAIL/Bokaro Steel Plant)Industrial ancillary & vendor supplyPower generationTownship services
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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