Sensi Career Intelligence

Overview

AI-powered career intelligence platform that deep-parses resumes and academic transcripts to construct a multi-dimensional competency profile and measure fit against real job opportunities.

The Problem

Job seekers often lack an objective way to measure how their credentials align with complex role requirements. Existing tools are fragmented - resume builders don't provide scoring, and job boards lack deep semantic analysis. For students, rich academic histories are often ignored by keyword-based filters, leaving their true potential invisible.

The Solution

Sensi leverages Large Language Models (LLMs) to perform structured skill extraction from both resumes and academic transcripts. It constructs a multi-dimensional competency profile across Technical Skills, Domain Knowledge, Soft Skills, and Academic Rigor. This profile is then visually cross-referenced against job descriptions in real-time.

Key Features

• AI Skill Extraction

  Deep parsing of resumes and transcripts into structured competency profiles using Gemini and OpenAI.

• Dynamic Radar Graph

  A visual centerpiece using Chart.js that overlays user profiles against job requirements for instant alignment feedback.

• Chrome Extension

  Real-time fit scoring directly over LinkedIn, Indeed, and Handshake job postings using Chrome Storage and content scripts.

• Progressive Toolkit

  Automatic generation of personalized cover letters and resume-edit suggestions triggered by high fit scores.

Hackathon Reflections

Built in under 12 hours, Sensi was an exercise in extreme prioritization. The core challenge was designing a 'radar-first' layout where a 6-axis chart remains the hero of the UI. I focused on building a 'progressive disclosure' model where advanced features - like AI-generated cover letters and specific resume edit recommendations - only unlock once a high fit score (65+) is achieved, ensuring users focus on roles where they have genuine alignment.

Deep Dive

Built in under 12 hours, Sensi was an exercise in extreme prioritization. The core challenge was designing a 'radar-first' layout where a 6-axis chart remains the hero of the UI. I focused on building a 'progressive disclosure' model where advanced features - like AI-generated cover letters and specific resume edit recommendations - only unlock once a high fit score (65+) is achieved, ensuring users focus on roles where they have genuine alignment.