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Girish Gaikwad

SDE & Creative Technologist

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[ SYS.ARCHIVE_RECORD ] - Evapro

> AI-powered evaluation system designed to automatically assess and grade flowcharts, algorithms, and pseudocode for academic and coding competitions.

// INDUSTRY_TAG
EdTech / AI Tooling
// DEPLOYMENT_YEAR
// SERVICE_PROTOCOLS
AI Evaluation Engine
ASSET_VIEWER_ACTIVE
Evapro hero image
// PROBLEM_STATEMENT

Challenge

Grading logic algorithms and flowcharts is highly subjective and format-dependent. To automate this, the system needed to interpret both visual and textual logic structures fairly:

>Parsing multiple proprietary file formats (.docx, .pptx, .pdf).

>Converting visual flowchart components into structured, evaluable logic strings.

>Ensuring a fair, rubric-based grading system rather than arbitrary AI assessment.

// SYSTEM_ARCHITECTURE

Solution

High level architecture of the application.

I engineered a multi-stage parser that extracts raw text and structural data from uploaded documents, passing the sanitized output to a rubric-bound AI scoring engine.

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    Universal Document Parsing: Integrated robust server-side document parsers capable of stripping text and structural logic from Word docs, PDFs, and PowerPoints, standardizing the input.

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    Weighted Rubric Engine: Restricted the AI's grading parameters by injecting strict evaluation rubrics into the prompt. The AI acts as a scoring algorithm utilizing weighted metrics rather than a free-form text generator.

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// DEPLOYED_MODULES

Technologies

React module

React

NodeJS module

NodeJS

LLM APIs module

LLM APIs

File Parsers module

File Parsers

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SYS.ADJACENT_MODULES

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