EXECUTE WORKS.

A curated deployment of robust systems, integrating advanced AI models and strict cryptographic protocols.

Veritas Health App

Engineered a Medical Misinformation Detection application leveraging advanced LLMs to identify hallucinations in medical claims and categorize information integrity.

FastAPI React LangChain LLM

chevron_right Developed backend pipeline utilizing FastAPI to interact with LangChain models.
chevron_right Built responsive React frontend for analyzing claims against medical databases.

veritas_analyze.py

from

langchain

import

PromptTemplate

import

fastapi

@app.post("/verify")

async def

analyze_medical_claim(claim: str):
prompt = PromptTemplate(template="Verify if {claim} is a medical hallucination.")
result =

await

llm_chain.arun(claim=claim)

return

{"status": "analyzed", "integrity_score": result.score}

Secure File Encryption

open_in_new

Designed a robust encryption utility implementing advanced cryptographic standards to secure sensitive file data at rest.

AES-256-GCM Cryptography Python

encrypt.sh

# Generating secure key...
$ generate_key --length 256
Key generated: [HIDDEN]

$ encrypt_file --input data.csv --algo AES-256-GCM
Status: SUCCESS
File locked. Integrity tag verified.

AI Face Recognition

open_in_new

Developed an automated face recognition system utilizing computer vision techniques to detect and authenticate facial features in real-time video streams.

OpenCV Computer Vision Python

detect_faces.py

import

cv2

import

face_recognition

video_capture = cv2.VideoCapture(0)

while True

:
    ret, frame = video_capture.read()
    face_locations = face_recognition.face_locations(frame)
    # Draw bounding box