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4 scoped briefs

2 mini · 2 major

AI & LLM Applications

Calling an LLM API is the easy part. The engineering is everything around it: chunking and retrieval that actually finds the right passage, evaluation so you can prove it improved, guardrails, cost control, and a fallback for when the model is wrong. That is what we teach and what we build.

PythonLangChainLlamaIndexOpenAI / Anthropic APIspgvectorFAISSFastAPINext.js
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The standard

Build the system. Understand every trade-off.

Every brief ends with working software, documented decisions, and evidence you can present—not a folder of code you cannot explain.

Two audiences, one engineering standard

Academic depth meets production discipline.

For students

Pick a brief below, or bring the problem statement your department handed you. We architect it with you, review every commit, deploy it to a real URL, and rehearse the viva until no question surprises you.

See student support

For companies

RAG over your own documents, support copilots, document extraction pipelines, agentic workflows, and evaluation harnesses so you can measure quality instead of guessing.

Discuss a company build

Mini projects

Focused scope. Real engineering.

Three to four weeks. Narrow enough to finish, deep enough that you learn the decision that actually matters.

2 briefs
Mini project3–4 weeks

RAG Chatbot Over Your Own Documents

Upload a corpus, ask questions, get answers with citations — and a retrieval evaluation report that proves it works.

PythonLangChainpgvectorFastAPI

You walk away with

  • Chunking + embedding pipeline
  • Answers with source citations
  • Retrieval eval set (precision@k)
  • Hallucination guardrail + refusal path
Mini project3 weeks

Resume Screener with Explainability

Rank candidates against a job description and, crucially, show why — with a bias audit on the output.

PythonLLM APIStreamlit

You walk away with

  • Structured extraction from PDF resumes
  • Scoring with per-criterion justification
  • Bias audit across a test set
  • Human-in-the-loop review screen

Major projects

Capstones you can defend.

Ten to twelve weeks. Architecture, trade-offs, failure modes, deployment, and evidence—the project that carries an interview.

2 briefs
Major project10–12 weeks

Multi-Agent Research Assistant

Planner, researcher, and critic agents that decompose a question, search, and adversarially verify each other before answering.

PythonLangGraphVector DBFastAPINext.js

You walk away with

  • Agent graph with tool calling
  • Adversarial verification pass
  • Token + cost budgeting per run
  • Trace viewer for every agent step
  • Evaluation harness with a scored benchmark
Major project10 weeks

Voice-Enabled Support Copilot

Speech in, grounded answer out, with escalation to a human when confidence drops below a threshold.

PythonWhisperLLM APIWebSocketsReact

You walk away with

  • Streaming speech-to-text
  • Grounded retrieval + confidence scoring
  • Human escalation handoff
  • Latency budget and p95 report

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Other engineering domains

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Python Full-StackJava & EnterpriseMachine LearningDeep LearningData EngineeringMobile AppsCloud & DevOpsCybersecurityIoT & EmbeddedJavaScript Full-StackVLSI & Chip DesignPower Electronics, EV & Energy SystemsSignal Processing & Wireless CommunicationsRobotics, Drones & Autonomous SystemsData Analytics & Business IntelligenceTest Automation & SDETComputer Networks & Protocol Simulation
Your next build starts here

Turn the idea into software people trust.

Bring us a product brief, a business problem, or a final-year project. We’ll turn it into a clear scope, a working build, and a handover you fully own.

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Prefer email? info@tenzok.in

Tenzok

A product engineering studio for ambitious companies, founders, and students who want real, production-minded work.

info@tenzok.in

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