Algo Trading Developer - Pine Script,MQL5 &Python Automation
Designed and implemented a robust webhook-based trading automation system that connects TradingView signals to real-time trade execution via the Tradovate API. The system is built using Python and handles signal reception, validation, and order execution in a seamless automated pipeline.
The architecture ensures low-latency communication, secure data handling, and reliable execution of trades without manual intervention. It processes incoming webhook alerts, applies validation logic, and triggers precise API-based trade execution.
Key features include:
• Real-time webhook signal processing (TradingView alerts)
• Python-based signal receiver and validation engine
• Secure and reliable API integration (Tradovate)
• Low-latency execution pipeline
• Fully automated trade workflow (zero manual input)
• Scalable design for multi-strategy integration
This solution is ideal for traders and firms looking to automate their strategies using webhook-driven architecture, enabling faster execution, reduced human error, and consistent performance in live trading environments.
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Developed an automated options trading bot using Python that executes trades on Deriv based on real-time strategy signals and multi-condition validation logic. The system is designed to operate continuously with minimal latency, ensuring fast and accurate trade execution in volatile market conditions.
The bot integrates signal generation, validation, and execution into a single automated workflow. It evaluates multiple technical indicators, applies strict entry conditions, and triggers trades only when high-probability setups are detected.
Key features include:
• Fully automated options trading (Deriv API integration)
• Real-time signal processing and execution
• Multi-indicator validation logic for higher accuracy
• Risk management controls and trade filtering
• Continuous operation with minimal manual oversight
• Scalable architecture for strategy customization
This solution enables traders to automate their options trading strategies end-to-end, improving consistency, speed, and discipline while eliminating emotional decision-making.
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Developed a fully automated trading system for MetaTrader 5 (MT5) that executes trades based on validated multi-indicator signals. The system integrates TradingView-generated signals with a Python-based processing engine, which evaluates multiple technical conditions before triggering precise trade execution.
The Expert Advisor (EA) is designed with advanced trade logic, risk management, and real-time execution capabilities. It ensures consistent performance by removing emotional decision-making and strictly following predefined rules.
Key features include:
• Automated trade execution on MT5 (buy/sell orders)
• Integration with external signal sources (TradingView via webhook)
• Multi-indicator validation (RSI, EMA, ADX, Volume, etc.)
• Built-in risk management (lot sizing, SL/TP control)
• Real-time processing with minimal latency
• Fully customizable strategy logic
This system enables traders to automate their strategies end-to-end — from signal generation to execution — ensuring speed, accuracy, and consistency in live market conditions.
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Engineered a high-performance Python-based trading signal engine designed to generate precise and reliable trade signals using multi-indicator confluence logic. The system evaluates over 12 technical indicators including RSI, EMA, ADX, Volume, and trend-based conditions to identify strong market opportunities while effectively filtering out noise and false signals.
The architecture is built to process real-time market data, validate multiple conditions simultaneously, and trigger only high-probability trade setups. This significantly improves signal accuracy and reduces unnecessary trades.
Key capabilities include:
• Multi-indicator confluence engine (12+ conditions)
• Real-time signal processing and validation
• False signal reduction using layered logic
• Scalable architecture for integration with trading APIs
• Seamless compatibility with automated execution systems (webhooks, APIs)
This system can be integrated with platforms like TradingView, Tradovate, or custom trading environments to enable fully automated trading workflows — from signal generation to execution.
Designed for traders and firms looking to achieve consistent, rule-based, and emotion-free trading through intelligent automation.
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AI Developer building AI Chatbots, Automation & Generative A
New to Contra
AI Developer building AI Chatbots, Automation & Generative A
Project Title
Samsung Washing Machine AI Support Chatbot
Problem Statement
Customers often face difficulties when using washing machines, especially when they encounter error codes, vibration, drainage problems, or maintenance issues. Finding the right solution from a user manual or contacting customer support can take time.
What the Chatbot Does
The Samsung Washing Machine AI Support Chatbot provides customers with quick and easy answers to common washing-machine questions. It acts as a digital support assistant that helps users understand problems and find appropriate troubleshooting information.
Key Uses
Explains common washing machine error codes
Helps users troubleshoot washing problems
Provides guidance for starting wash cycles
Helps with vibration and noise-related issues
Provides drainage and drain-filter guidance
Gives cleaning and maintenance information
Helps users understand common machine problems
Provides quick answers without searching through lengthy manuals
Main Benefit
The chatbot makes washing-machine support faster, easier, and more accessible, helping customers find relevant troubleshooting information when they need it and reducing the need for repeated customer-support enquiries.
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Problem Statement
Students and parents often have questions about courses, admissions, placements, hostel facilities, campus facilities, transportation, and other college services. Finding the right information can take time and may require contacting different departments.
What the Chatbot Does
The College AI Assistant provides a simple way for students and parents to get quick answers to their college-related questions. It works as a digital college information assistant that is available whenever they need help.
Key Uses
• Provides information about courses and programs
• Helps with admission-related enquiries
• Answers questions about placements
• Provides hostel and campus facility information
• Shares transportation and student support information
• Helps users find relevant college information quickly
• Reduces repetitive enquiries handled by college staff
• Makes important information easier for students and parents to access
Main Benefit
The chatbot makes college information quick, accessible, and easier to understand, while helping the college reduce repetitive enquiries and provide better support to students and parents.
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Project Title
AI Voice Appointment Assistant
Problem Statement
Traditional appointment systems often require users to type information, select dates and times, search for existing appointments, and remember upcoming bookings.
This can be time-consuming, especially for people who prefer a simple voice-based interaction.
What the AI Assistant Does
The AI Voice Appointment Assistant allows users to manage appointments simply by speaking naturally.
Users can ask the assistant to:
📅 Book an appointment
❌ Cancel an appointment
🔄 Reschedule an appointment
📋 View their appointments
📧 Receive email confirmation
🔊 Receive a voice response
⏰ Get appointment reminders
For example, a user can simply say:
“Book an appointment for Anusha tomorrow at 5 PM.”
The assistant understands the request and helps complete the appointment process.
Key Benefits
For Customers
Hands-free appointment booking
Easy natural voice interaction
Faster appointment management
Easy cancellation and rescheduling
Appointment confirmation
Reminder support
For Businesses
Reduces repetitive appointment enquiries
Automates routine scheduling tasks
Improves customer experience
Provides convenient 24/7 appointment assistance
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Developed an AI-powered Beauty Parlour Receptionist that provides 24/7 customer assistance through a natural conversational interface. The solution helps customers get information about services, submit appointment requests, and receive instant responses.
A dedicated owner dashboard enables the salon team to manage incoming appointment enquiries and monitor customer interactions from a centralized interface.
The solution is designed for reliable conversational assistance, structured customer information handling, session-based interactions, and scalable customer support.
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AI automation & AI agent developer from Chennai, India
New to Contra
AI automation & AI agent developer from Chennai, India
Stop re-typing invoices one field at a time.
DocIntel reads invoices and purchase orders into structured data. Every value is checked in code (format, dates, whether it appears on the page), and anything doubtful goes to a review queue with the source page beside it. A person corrects it, and the original value is kept on record.
• On a real model (Claude Haiku 4.5): 387 of 390 fields correct on 30 synthetic invoices, one run; 2 wrong values were not flagged for review (both on image-only scans)
• The video shows a selected example: a date the model misread, caught by a date check
• 658 automated tests; Python, FastAPI, PostgreSQL
Fictional invoices. Want your invoices read for you? Message me.
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Let an AI take booking conversations, with the risky rules enforced in code.
VoiceDesk is the brain of an AI receptionist: it checks a real calendar, books, reschedules and cancels appointments, takes messages and asks the team to call back. The model can only change a booking that a lookup by name and phone number handed it, so a wrong-number caller can't cancel someone else's appointment. Voice and phone are not connected yet; everything shown is typed text.
• On a real model (Claude Haiku 4.5): 10 of 12 task scenarios and 5 of 5 safety-only passed (a do-nothing receptionist also passes those 5); one run, 17 scripted scenarios
• Not caught by the checks: once it said a taken slot was free (nothing changed), and once it cancelled before the caller confirmed
• 1,929 automated tests; Python, PostgreSQL
Fictional salon. Want an AI receptionist for your business? Message me.
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Ask your company's documents a question and get an answer you can check.
KnowledgeOS answers only from your own documents and shows the passage behind every claim. Before anyone sees an answer, code checks that each citation points at evidence the model was actually given; if not, the answer is thrown away. If the documents don't cover the question, it says so instead of guessing.
• On a real model (Gemini): 32 of 33 answers passed the citation check, and 12 of 45 answerable questions got no answer (a known cost of the strict threshold)
• 52 test questions written by AI and approved by me, on fictional documents; one run
• 1,314 automated tests; Python, PostgreSQL + pgvector
Want answers from your own documents? Message me.
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Stop copying enquiries from your inbox into your CRM by hand.
This AI agent reads each business email, works out who it's from and what they want, matches them to your CRM, and drafts a reply. Nothing changes in your CRM until you approve it, and in this version replies are drafted, never sent.
Every detail is quoted from the email, or it's dropped
Emails that try to instruct the assistant go to a person, not into your CRM (in my latest real-model run, all 12 test attack emails did)
1,103 automated tests, plus real-model checks on Gemini: 0 unsafe actions planned in 21 plans. Accuracy on a real model is lower than on my test mock, and the case study shows the numbers and their limits.
Demo uses invented data. Want this for your inbox? Message me.
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Turning clicks into customers with high-converting web desig
New to Contra
Turning clicks into customers with high-converting web desig
