About
A student exploring intelligent systems.
I'm Darshil Modi, a B.Tech student at Adani University interested in artificial intelligence, multi-agent systems, and emerging technologies. My projects focus on solving practical problems in education, agriculture, and talent intelligence through AI-driven systems. Beyond technology, I'm fascinated by space exploration and the engineering challenges that shape humanity's future. Currently serving as a Google Student Ambassador (2026-2027).
National-level hackathon finalist.Missions
Build logs from the frontier.
Projects are framed as missions: practical systems, clear problems, and a record of how each one is being built.
Mission 01Flagship Mission
TalentAI-X
An AI talent intelligence system for reading stronger signals from skills, projects, and candidate evidence.
Overview
TalentAI-X is the flagship mission: a system designed to make talent discovery more evidence-driven by combining profile intelligence, project context, and AI-assisted evaluation.
Problem
Talent evaluation often collapses people into keywords, resumes, and surface-level filters. That makes it easy to miss practical ability and difficult to compare candidates fairly.
Solution
TalentAI-X treats projects, skills, and context as signals. The system structures those signals, evaluates them through intelligent workflows, and presents clearer fit insights for decision makers.
Next.jsReactTypeScriptAI AgentsSupabaseOpenAI/Gemini
01Profile Intake
02Signal Extraction
03Agent Evaluation
04Fit Scoring
05Decision Dashboard
Mission 02Applied AI
Agri-Sage
An agriculture-focused assistant for practical crop, field, and advisory workflows.
Overview
Agri-Sage explores how AI can support agriculture decisions with contextual recommendations and clearer access to field knowledge.
Problem
Farmers and field operators often need timely guidance, but useful information can be scattered, technical, or hard to apply in local conditions.
Solution
The mission focuses on turning agricultural inputs into structured guidance, helping users reason through crops, risks, and next actions.
AIReactTypeScriptSupabaseOpenAI/Gemini
01Field Context
02Knowledge Layer
03Reasoning Flow
04Recommendation
05Action Log
Mission 03Learning Systems
EduMentor
A learning companion concept for personalized guidance, study paths, and student support.
Overview
EduMentor is focused on education workflows where students need direction, structure, and feedback that adapts to their progress.
Problem
Students often know they need to improve, but not what to study next, how to prioritize, or how to convert feedback into a learning plan.
Solution
EduMentor organizes learning goals, recommends next steps, and supports students with AI-driven mentoring loops.
Next.jsReactTypeScriptAISupabase
01Student Goal
02Assessment
03Learning Path
04Mentor Loop
05Progress Review
Mission 04Language AI
Linguamate
A language learning mission built around practice, feedback, and communication confidence.
Overview
Linguamate explores language practice through AI-assisted conversations, feedback, and learning routines.
Problem
Language learners need repetition and feedback, but consistent practice partners and useful corrections are not always available.
Solution
Linguamate creates a guided practice loop where learners can speak, review, and improve with context-aware support.
ReactTypeScriptAIOpenAI/Gemini
01Practice Prompt
02Conversation
03Feedback
04Revision
05Learning Memory
Mission 05Future Tech
Cyborg Nexus
A future-facing exploration of human-computer interaction and intelligent augmentation.
Overview
Cyborg Nexus is a concept mission around the future of augmentation, interfaces, and systems that extend human capability.
Problem
As intelligent tools become more capable, the hard question is how to design systems that amplify human intent instead of adding friction.
Solution
The mission studies interface ideas, automation flows, and AI-assisted workflows that keep humans in control.
Three.jsReactTypeScriptAIGSAP
01Human Intent
02Interface Layer
03AI Mediation
04System Action
05Feedback
Research Log
Notes in preparation.
Research logs are currently being prepared. I'm documenting lessons from building multi-agent systems, AI applications, software architecture, and future technologies.
First entries arriving soon.
