AI & Machine Learning
We design and build AI-powered systems that solve real business problems — from predictive analytics and natural language processing to ensemble machine learning models and intelligent automation. Our approach combines deep ML expertise with production engineering to deliver systems that scale.
What We Build
Predictive Analytics
ML ensembles that forecast trends, detect anomalies, and score risk using your historical data.
NLP & Text Analysis
Sentiment analysis, document classification, and entity extraction from unstructured text.
AI-Powered Applications
Chatbots, recommendation engines, and intelligent search powered by Claude, Gemini, and open-source models.
ML Infrastructure
Training pipelines on Vertex AI, model serving, A/B testing, and monitoring in production.
Case Study: BullishBeat.ai
BullishBeat.ai
AI-Powered Stock Prediction & Trading Platform
BullishBeat.ai is a full-stack ML platform we built from scratch — predicting stock movements across 500+ S&P 500 symbols using a 6-algorithm ensemble trained on 101 features. The system runs 24/7 with real-time data processing, automated scanning, AI-powered analysis, and paper trading with broker integration.
Machine Learning Pipeline
BullishBeat.ai's prediction engine uses a weighted ensemble of 6 algorithms, each independently trained and hyperparameter-tuned via 20-iteration random search with 3-fold time-series cross-validation. Models that overfit (AUC > 0.95) are automatically rejected.
61 technical indicators + 40 enrichment features (earnings, fundamentals, sector rotation, sentiment, options flow). AUC-weighted ensemble with GPU model bonus weighting.
Real-Time Data Processing
BullishBeat.ai processes market data in real-time via Polygon.io WebSocket and REST APIs. The system handles streaming quotes, trades, and aggregates across 500+ symbols simultaneously.
WebSocket Streaming
Live price feeds via Polygon.io WebSocket — sub-second updates for active symbols during market hours.
REST Batch Fetching
Parallel historical data fetch with 50 concurrent connections. 5-year history for training, daily updates for prediction.
Webhook Processing
Railway deployment webhooks trigger auto-rebuild on git push. Vertex AI job completion webhooks trigger model download and hot-swap.
Redis Job Scheduling
Redis-backed scheduler with weekdays_only and market_hours flags. Scanner, training, enrichment, and snapshot jobs run autonomously.
AI Automation & Multi-Provider Intelligence
BullishBeat.ai integrates three AI providers for different analysis tasks. Each provider is selected based on its strengths — Claude for deep reasoning, Gemini for multimodal analysis, Llama for fast inference.
- ✓ Claude (Anthropic) — Stock analysis reports, earnings interpretation, risk assessment with 200K context window
- ✓ Gemini (Google) — Chart pattern recognition, financial document analysis, sentiment scoring
- ✓ Llama (Groq) — Sub-second inference for real-time signal generation during market hours
AI-powered portfolio management with automated position sizing, stop-loss optimization, and swing trade exit intelligence.
Automated Background Scanner
BullishBeat.ai's background scanner runs continuously during market hours, cycling through 500+ S&P 500 stocks. It fetches fresh data, runs the ML ensemble, generates BUY/SELL signals, and pushes notifications — all without human intervention.
Scanner Loop
Scans all S&P 500 symbols every market session. Configurable batch size and intervals.
Signal Generation
ML predictions + AI analysis combined into BUY/SELL/HOLD signals with confidence scores.
Notifications
Push notifications via WhatsApp and web push when high-confidence signals are detected.
BullishBeat.ai Tech Stack
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Google Cloud & Vertex AI
We are experienced Google Cloud practitioners. Our ML training pipelines run on Vertex AI with L4 GPU instances for cost-effective, high-throughput model training. We handle the full lifecycle:
Vertex AI Custom Jobs
Container-based training with auto-scaling, GPU selection (L4, T4, A100), and job scheduling.
GCS Model Storage
Models stored in Google Cloud Storage with versioning. Railway/Vercel workers download and serve.
BigQuery Integration
Feature engineering and analytics at petabyte scale with BigQuery ML and scheduled queries.
Cloud Functions + Pub/Sub
Event-driven ML pipelines: data arrives, triggers preprocessing, launches training jobs.
AI Integration Services
We integrate leading AI providers into your applications:
- ✓ Claude (Anthropic) — Long-context analysis, document processing, code generation
- ✓ Gemini (Google) — Multimodal AI, Vertex AI training pipelines
- ✓ Llama (Meta/Groq) — Fast inference for real-time applications
- ✓ Custom chatbots — AI assistants embedded in your product, trained on your data