Anya Rajesh
Building and deploying full-stack AI solutions that integrate real-time data pipelines, retrieval-augmented generation, and privacy-first architectures. Focused on creating impactful, accessible applications that solve real problems.
Vigil AI
Intelligent Cybersecurity Monitoring System
What is Vigil AI?
Vigil AI is an open-source, AI-native cybersecurity monitoring platform designed to help organizations detect threats before they become incidents. It combines machine learning anomaly detection, real-time log analysis, and intelligent alerting into a unified security operations toolkit.
Built on a FastAPI backend with React frontend, Vigil processes raw log streams from any source — web servers, firewalls, cloud platforms — and applies trained models to surface anomalies, suspicious patterns, and potential intrusions in real-time.
Core Capabilities
Real-Time Threat Detection
Continuously monitors system logs, network traffic, and user behavior using ML anomaly detection algorithms to identify threats the moment they emerge.
AI-Powered Behavioral Analysis
Trained on thousands of attack patterns, Vigil AI understands the difference between normal activity and subtle indicators of compromise (IoCs).
Intelligent Dashboard
Visual threat maps, risk scoring, incident timelines, and alert prioritization — all in a clean, operator-friendly interface built for speed.
Automated Incident Response
When a threat crosses confidence thresholds, Vigil can automatically trigger response playbooks: isolating hosts, revoking credentials, and generating reports.
MITRE ATT&CK Mapping
Every detected event is mapped to the MITRE ATT&CK framework, giving security teams immediate context on attacker tactics, techniques, and procedures.
Multi-Source Log Ingestion
Ingests from web servers, firewalls, SIEM systems, cloud providers, and custom endpoints via a unified Elasticsearch-backed pipeline.
Tech Stack
MedInsight AI
Intelligent Medical Diagnostics & Health Analytics Platform
What is MedInsight AI?
MedInsight AI is an intelligent medical analytics platform that bridges the gap between raw patient data and actionable clinical insight. Designed for healthcare professionals, students, and researchers, it uses advanced NLP and machine learning models to assist with disease identification, health risk assessment, and medical literature discovery.
The platform's symptom-driven diagnostic engine processes hundreds of clinical indicators simultaneously, providing ranked differentials with confidence scores and relevant medical context — reducing diagnostic guesswork and supporting faster, better-informed clinical decisions.
Core Capabilities
Symptom-Based Disease Prediction
Select symptoms from a comprehensive library and receive AI-powered differential diagnoses ranked by probability, with supporting clinical context.
Patient Data Analytics
Upload patient vitals, lab results, or historical records and receive trend analysis, outlier detection, and risk stratification powered by ML models.
Medical Literature Synthesis
Integrates with PubMed and Semantic Scholar to surface relevant research papers, clinical trials, and treatment guidelines for any queried condition.
Drug Interaction Checker
Cross-references prescribed medications against a drug interaction database, flagging contraindications and adverse combination risks automatically.
Clinical Report Generation
Automatically generates structured clinical summaries, SOAP notes, and patient-friendly plain-language explanations from raw diagnostic data.
Privacy-First Architecture
HIPAA-aligned design with local inference options, data anonymization pipelines, and audit logging to protect sensitive patient information.