Flagship Product Launches.
Translatify - AI Translation Suite
System Architecture
Client React container feeds user text/speech input to a Node.js middleware. The backend proxies translation tasks to pre-trained transformer pipelines on HuggingFace, caching repeated phrases in localized caches.
Key Capabilities
- Real-time dual translation stream for voice-to-text inputs.
- Localized client-side caching of translated assets to bypass API delays.
- Custom route gateways filtering repetitive input strings.
Engineering Challenge
Reducing inference API latency for interactive speech. Solved by implementing client-side caching maps and a debounce queue for voice packets.
Impact & Business Value
Decreased translation delay by 40% for repetitive queries, optimizing third-party model inference usage rates.
Future Scope
Integrating localized offline model configurations using ONNX runtimes in the browser.
Stroke Risk Clinical Predictor
System Architecture
Takes input parameters (clinical diagnostic indicators) via a REST API. Evaluates raw features using trained Random Forest and Logistic Regression classifiers, returning calculated risk coefficients.
Key Capabilities
- Preprocessed demographics and clinical histories (glucose levels, heart rate metrics).
- Feature correlation maps exposing relative statistical impact.
- RESTful endpoint integration for external EHR software bindings.
Engineering Challenge
Handling extreme class imbalance where stroke positives made up under 5% of raw datasets. Solved by applying SMOTE (Oversampling) and auditing threshold calibrations.
Impact & Business Value
Achieved 92% classification accuracy, establishing diagnostic pre-screening viability.
Future Scope
Training neural networks on dense medical charts and deploying models to containerized environments.
MERN Grocery eCommerce Platform
System Architecture
React SPA handles layouts and shopping cart state. An Express server controls JSON endpoints, managing authentication (JWT) and cart persistence on a MongoDB backend.
Key Capabilities
- Secure session flows and token-based client credentials.
- Scalable inventory modeling with real-time stock deductions.
- Dynamic search queries routing index filters in MongoDB.
Engineering Challenge
Resolving transaction conflicts when concurrent checkouts target identical limited inventories. Solved by writing transactional queries.
Impact & Business Value
Delivered a zero-leak checkout database module with fast page load performance.
Future Scope
Configuring webhooks to automatically adjust inventory based on supplier notifications.
MBTI Written Personality Predictor
System Architecture
Cleans and preprocesses written text samples, parses tokens into TF-IDF vector structures, and runs gradient-boosted multi-class classification nodes to predict Myers-Briggs indicators.
Key Capabilities
- Text preprocessing module stripping emojis, URLs, and excessive stop words.
- TF-IDF tokenizers mapping feature sets of frequent phrases.
- Multi-class XGBoost models returning statistical distributions of personality traits.
Engineering Challenge
High-entropy text datasets with varied sentence structure. Solved by tuning tf-idf parameters and deploying structural regularization checks.
Impact & Business Value
Reached 85% validation alignment, demonstrating utility for automated client targeting dashboards.
Future Scope
Fine-tuning transformer topologies (BERT) to extract structural emotional semantics.
E2E Banking Data Audit & Analytics
System Architecture
Extracts bank logs, cleans records using SQL staging schemas, constructs dimensional models, and builds Power BI dashboards displaying key indicators.
Key Capabilities
- Custom SQL schemas consolidating raw account records into unified datasets.
- Interactive BI filters parsing indicators (e.g. credit scores, transaction frequency).
- Advanced DAX metrics charting active customer churn probability rates.
Engineering Challenge
Modeling convoluted banking logs containing circular account dependencies. Solved by staging standard Star Schemas.
Impact & Business Value
Isolated attrition causes, identifying indicators that supported banking campaigns to reduce churn by 18%.
Future Scope
Setting up automated scheduled dashboard updates using DirectQuery pipelines.
Real-Time Sentiment Monitoring Engine
System Architecture
Connects to real-time streams via Tweepy, parses incoming text strings through TextBlob lexicon filters, and outputs statistical sentiment scores.
Key Capabilities
- Real-time API parser with automatic rate-limit filtering.
- Text sentiment score indicators returning positivity/negativity splits.
- Automated matplot data visualizations plotting logs dynamically.
Engineering Challenge
Managing high rate-limiting restrictions and cleaning short, noisy text strings. Solved by configuring backoff timers and regex pre-filters.
Impact & Business Value
Operated as a functional brand tracker, enabling instant reputation indicators.
Future Scope
Migrating to Apache Kafka to handle massive streaming data loads.