AI Voice Mentoring

Your AI mentor, available 24/7

Yukti gives students and teams access to specialist AI voice mentors — data engineering, ML architecture, presentations, and domain expertise — to sharpen skills and refine solutions.

Select your mentor
SenthilDomain
KavithaData
RajanML/AI
LakshmiPresenting

Mentors

A mentor for every challenge

S

Senthil

Project Domain Expert

Helps you structure technical thinking, identify project gaps, and articulate why your solution matters. Deep knowledge across industry domains — healthcare, agriculture, fintech, manufacturing.

Project ScopingTechnical ThinkingFeasibilityTamil + English
K

Kavitha

Market Feasibility & Pitch Practice

Tests whether your idea is viable, challenges your market assumptions, and helps you practice pitching to judges. Asks the hard questions before evaluators do.

Market FitPitch PracticeCompetitionTamil + English
R

Rajan

ML & AI Specialist

Model selection, evaluation methodology, and result interpretation. Coaches you to explain complex ML decisions in plain language that non-technical judges understand.

Model DesignEvaluationExplainabilityTamil + English
L

Lakshmi

Presentation Coach

Presentation structure, technical storytelling, and Q&A preparation. Coaches you to clearly communicate your approach and defend your decisions with confidence.

SlidesQ&A PrepCommunicationTamil + English

Process

From sign-in to insight in minutes

01

Sign in

Your faculty coordinator creates your account. Sign in and you're ready.

02

Pick a mentor

Choose the mentor that fits your current need — data engineering, ML architecture, presentation prep, or domain context.

03

Refine your solution

Have a live voice conversation. Get actionable feedback to strengthen your project.

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Topics Covered

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Industry Domains

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Avg Response Time

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Mentor Specialists

Experience

Like talking to a real mentor

Natural voice conversations with actionable takeaways.

I'm working on the TANGEDCO transformer failure prediction problem but my dataset has a lot of missing sensor readings and class imbalance.

You

Kavitha is thinking...

Good that you've identified both issues upfront! Let's tackle the missing data first — what percentage of readings are missing, and is it random or systematic? That determines whether we impute or restructure.

Kavitha

Action Items

  • Analyse missing data patterns (MCAR vs MNAR)
  • Try SMOTE or class-weighted loss for imbalance
  • Build baseline model on raw data before enrichment

Testimonials

What students are saying

Kavitha helped us identify systematic bias in our textile defect dataset. In one session, she walked us through feature engineering techniques that improved our data quality score by 30%. The action items were specific and immediately useful.

Deepika S.

Data Engineering Student

Rajan helped us choose the right evaluation methodology for our transformer failure prediction model. He explained the trade-offs between precision and recall in our context and suggested a custom metric that the reviewers loved.

Karthikeyan R.

ML Engineering Student

Lakshmi completely transformed our final presentation. She taught us how to structure our technical story so the audience could follow our approach, and drilled us on tough Q&A scenarios. We felt confident walking into the presentation.

Anitha M.

Final Year Student

Features

Everything you need to prepare

Real-Time Voice AI

Natural conversations powered by GPT-4o. Get instant expert guidance anytime during the mentorship window.

Personalized Feedback

AI-generated action items and next steps after every session.

Session History

Full transcripts and progress tracking across all your mentoring sessions.

Time Budget Tracking

Your institution controls mentoring time allocation per team.

Ready to level up your project?

Sign in with your institution-provided account and start a mentoring session.

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