Market Intelligence Dashboard for NIFTY, BankNifty & Sensex

@sajjadtaghvaeifr

Hello, I trust you're doing well. I am well experienced in machine learning algorithms, with nearly a decade of hands-on practice. My expertise lies in developing various artificial intelligence algorithms, including the one you require, using Matlab, Python, and similar tools. I hold a doctorate from Tohoku University and have a number of publications in the same subject. My portfolio, which showcases my past work, is available for your review. Your project piqued my interest, and I would be delighted to be part of it. Let's connect to discuss in detail. Warm regards. please check my portfolio link: https://www.freelancer.com/u/sajjadtaghvaeifr

@vishal1145

Your platform will fail if the data pipeline can't handle NSE's rate limits during market hours. I've built 3 real-time trading dashboards that process 50K+ ticks per second without dropping packets. Quick question - are you pulling live option chain data via NSE API or using a paid vendor like Upstox? The architecture changes completely based on latency requirements. Also, what's your expected concurrent user load - 100 or 10,000? Here's the architectural approach: - PYTHON + FASTAPI: Build async endpoints with WebSocket streaming for real-time market data. Use Celery workers to calculate RSI, VWAP, EMA indicators without blocking API responses. - POSTGRESQL + TIMESCALEDB: Store tick data in hypertables optimized for time-series queries. This cuts query time from 8s to 300ms when analyzing historical option chain patterns. - FLUTTER WEB: Implement state management using Riverpod to prevent UI freezes when rendering 50+ charts simultaneously. Use canvas-based charting libraries for smooth 60fps updates. - DATA PIPELINE: Set up Redis caching layer to handle NSE's 3-request-per-second limit. Queue market data ingestion to avoid API bans during volatile sessions. - SENTIMENT ENGINE: Integrate NLP models (FinBERT) to score news headlines. I've deployed similar systems that achieved 78% accuracy in predicting intraday moves. I've architected similar platforms for 2 prop trading firms that scaled from backtesting to live execution. Let's discuss edge cases like handling market circuit breakers and data gaps before locking the scope.

@mykhaylob4

✋ Hi there. I can build your market intelligence dashboard for NIFTY, BankNifty and Sensex with real-time analytics and sentiment scoring. ✔️ I have built similar financial analytics platforms with Flutter web frontend and Python FastAPI backend. I will develop a dashboard that collects and analyzes index data, option chain, indicators and global markets, implement engines for sentiment, trade opportunity and risk scoring, and build a user login system with admin panel. Click the chat button and I can share my recommended architecture, timeline and similar projects. Best regards, Mykhaylo

@techsty2014

Good to see this project, We will build your market intelligence dashboard with Flutter Web, FastAPI, and PostgreSQL: sentiment engine, risk scoring, confidence scoring, and trade opportunity detection across NIFTY, BankNifty, and Sensex. For the data pipeline, we will schedule parallel fetches for Option Chain, OI, PCR, VIX, and global indices. Each feed will normalize into a shared schema so the scoring engines process a consistent data model. This keeps latency low and makes adding new indicators simple. A couple of quick things to confirm: 1) Which data providers do you prefer for Option Chain and OI (NSE direct, or a third-party API)? 2) Should the sentiment engine parse news headlines using an LLM, or will keyword scoring suffice for Phase 1? The number quoted here is a starting estimate. Looking forward to potentially working together. Thanks, Faizan

@Shrutibimpl

Hello, I will develop your web-based market intelligence platform using your preferred technology stack. I will build the frontend application using Flutter Web to deliver a highly responsive dashboard, and implement the backend engine using Python FastAPI backed by PostgreSQL. I will set up ingestion pipelines to fetch real-time index data, India VIX, global markets, and option chain metrics like open interest and PCR. I will write custom backend logic to calculate standard indicators, parse news headlines, and compute your target bullish/bearish percentages, sentiment scores, and risk ratings. The platform will classify market conditions into trade, caution, or no-trade zones and include a secure login system and an administrative console. 1) Do you have preferred financial API providers or broker credentials ready for fetching the option chain, indicators, and global index data? 2) Should the sentiment scoring algorithm utilize a pre-trained natural language processing model for news analysis, or a rules-based scoring approach? 3) Which cloud hosting environment do you prefer for deploying the Python FastAPI services and PostgreSQL database? Thanks, Bharat

@axiomswb

Architecting your Market Intelligence Dashboard... I see you need a high-performance Python FastAPI backend to aggregate complex live data (Option Chains, VIX, Global Indices) and feed it into a responsive Flutter Web frontend. Building custom scoring engines for financial data is my specialty. Recommended Architecture & Execution Plan: Data Ingestion (FastAPI): Async API routes to pull NSE & Global Markets data without lagging the system. Scoring Engines: Utilizing Python (Pandas/NumPy) to crunch technical indicators (RSI, VWAP, EMA) and output your exact signals: Trade Opportunity, Caution Zone, and No Trade Zone, plus Sentiment/Risk percentages. Database (PostgreSQL): Securely manage User Logins, Admin RBAC, and store historical market logs. Frontend (Flutter Web): A clean, modular dashboard to visualize these complex data streams intuitively. Cost & Timeline: I can deliver this Phase 1 MVP within 21 to 30 days for ₹145,000 INR. (Please see my profile for recent complex web application builds). I am ready to start mapping the PostgreSQL schema today. Quick technical question: For the real-time NSE and Global Market data, do you already have a preferred paid API provider mapped out (like TrueData or Kite Connect), or will I need to build web-scrapers/unofficial API hooks for the Phase 1 MVP?

@mrresearcher99

Hello Sir, I have 5 years of experience working with Python Development. Let's discuss this further. Thanks, Bhargav.

@KrisuTechkul

Krishna here from Delhi and I represent a team of highly skilled AI and software development experts. Our expertise aligns perfectly with your requirements as we have a successful track record of delivering advanced, tailor-made AI solutions for financial analysis and data-driven business decision-making. Over the years, we have built intricate applications that process and analyze copious amounts of data, just what you need for this project. Our knowledge of FastAPI, Python, and Web Application development ensures a smooth, efficient, and robust system that seamlessly integrates front-end Flutter web components with a highly scalable PostgreSQL back-end. One key differentiating factor is our appreciation for the value of meaningful information over overwhelming data. We would prioritize building a user-friendly Market Intelligence Dashboard that intelligently presents key outputs like Trade Opportunities, Market Sentiment Score, Risk Score, Confidence Score, and more. Let's transform complex market insights into actionable intelligence together! Lastly, our commitment to meeting deadlines without compromising on quality is something our previous clients can vouch for. We will work closely with you throughout the project lifecycle to ensure each deliverable meets your expectations.

@nexvative

Hello, Your project aligns closely with my experience in financial analytics platforms, Python backend development, real-time market data processing, and AI-driven decision-support systems. I can develop a scalable Market Intelligence Dashboard using Flutter Web, FastAPI, and PostgreSQL that aggregates market data from multiple sources and transforms it into actionable market intelligence rather than direct trading signals. Proposed Architecture: • Flutter Web frontend with responsive dashboards and visual analytics • FastAPI backend for data ingestion, indicator calculations, scoring engines, and APIs • PostgreSQL for historical market data, sentiment records, and user management • Background workers (Celery/APScheduler) for scheduled data collection and processing • Modular analytics engine for easy Phase 2 expansion Phase 1 Modules: ✔ NIFTY, BankNifty, Sensex & Gift Nifty Analysis ✔ India VIX Monitoring ✔ Option Chain & Open Interest Analysis ✔ PCR, Volume, RSI, VWAP & EMA Calculations ✔ Global Market Intelligence (Dow, Nasdaq, S&P500, DAX, FTSE, Hang Seng, Kospi) ✔ Financial News Aggregation & Sentiment Analysis ✔ Market Sentiment Engine ✔ Risk Score Engine ✔ Confidence Score Engine ✔ Trade Opportunity Classification (Opportunity / Caution / No Trade) ✔ User Authentication & Admin Dashboard Expected Outputs: • Bullish/Bearish Percentage • Market Sentiment Score • Risk Score • Confidence Score • Market Opportunity Classification

@FreeLancers360

Hi, Your project "Market Intelligence Dashboard for NIFTY, BankNifty & Sensex" caught my eye because it lines up so closely with what we build. From your brief I can see this involves web app, frontend, backend — all areas we handle in-house. We specialise in Python, PostgreSQL, Financial Analysis, Web Development, which lines up directly with what you need. How we'd approach it: - Map out the scope, pages and data models up front - Build the frontend and backend with clean, scalable code - Test across devices and browsers, then deploy - Hand over with documentation and post-launch support Delivering at the scale of 50 analysis is no problem for us — we're set up for volume without dropping quality. I can have this delivered in about 7 days. If it helps, I can share a couple of relevant samples and a short plan before you decide. Looking forward to it. Best regards, FreeLancers360

@Sahyadri96

Completed projects till now 1) Python + DhanAPI +Excel + VBA option scalping strategy 2) Python 21 EMA and 9 EMA crossover strategy on DhanAPI 3) Google sheet + FyersAPI trading 4) Google sheet + Algomojo + Upstox 5) Tradetron Banknifty option scalping strategy 6) Excel 2600 NSE 10 years data 7) Copytrading using python 8) Tradetron Supertrend + MACD Crossover Strategy 9) Dhan option chain with Greeks in Google spreadsheet via Google Appscript 10) Backtesting of Nifty options for wait and trade strategy 11) Trigger orders for Dhan Nifty options 12) Shoonya API:- Wait and trade strategy 13) Tradetron: RSI + ADX + EMA strategy 14) Python Moving avarage channel trading Algo 15) Kotak Neo: Turtle scalping strategy for options 16) Fyers Filtered option chain in Excel 17) Binance Bitcoin tradingview strategy python bot 18) Fyers Tradingview python bot 19) Dhan Python order manager I can deliver any project in Trading. Readymade setups for Python available

@gloifytech

Gloify specializes in AI-powered analytics platforms, combining expertise in Python, FastAPI, Flutter, and data visualization. We can build your market intelligence dashboard with scalable data pipelines, sentiment and risk engines, real-time market analysis, and secure role-based access. Our approach includes integrating market, options, and news data into actionable insights with clear confidence scoring and intuitive dashboards. We’ll recommend a modular architecture using Flutter Web, FastAPI, and PostgreSQL for long-term scalability. Which market data providers or APIs do you plan to use?

@tamannarajput18

Having worked extensively as a Full Stack Developer with a specific focus on MEAN and MERN stack development, I am well-positioned to deliver the robust and scalable market intelligence platform you require. For this project, I propose using Flutter Web as the frontend, and Python FastAPI in conjunction with PostgreSQL for the backend and database respectively. In addition to my web development skills, my experience in creating automated workflows using n8n will be beneficial for generating real-time analytics from sources such as NIFTY, BankNifty, Sensex et al. and computing the outputs like Risk Score or Confidence Score you seek. Lastly, my technical expertise extends beyond just building applications to ensuring their optimal performance and security by practices like code refactoring and applying standardised authentication protocols. In short - if you're looking to have an analytic platform that not only gathers market data but provides insightful opportunities and indications from it with a high-performance backend architecture then I'm your ideal candidate

@iterativeTech

As an AI and cloud data engineering specialist, I'm uniquely positioned to deliver the intelligent system that your market intelligence platform requires. My extensive experience in finance aligns perfectly with your project, allowing me to bring valuable insights that could boost your ROI. My core services in AI/ML development and cloud data engineering are a great match for building and optimizing the scalable systems you desire, while my expertise in real-time analytics and business intelligence gives me the ability to provide live operational and strategic insights. In particular, I'm well-versed in all aspects of your technology preference, from Flutter Web on the frontend to Python FastAPI on the backend, ensuring the smooth creation of your market intelligence platform. Additionally, my proficiency in using PostgreSQL will facilitate the efficient collection and analysis of crucial market data from different sources. Lastly, my approach is always business-oriented - focusing on outcomes rather than just implementations. I prioritize creating technical solutions geared towards growth and tangible results like faster processes, lower costs, enhanced customer experiences, and scalability. With my skills, experience, and commitment to delivering value, I guarantee a high-quality product that meets your requirements and exceeds your expectations.

@dushyant317

I can help build a scalable AI-powered market intelligence platform using Flutter Web, FastAPI, and PostgreSQL with real-time market data ingestion, sentiment and risk engines, analytics dashboards, and a modular architecture designed for future AI enhancements and trading intelligence features.

@mubashir021

Hello, your project on building an AI-Powered Market Intelligence Dashboard for NIFTY, BankNifty, and Sensex is intriguing, and I have the expertise to bring this complex analytics platform to life. I am Mubashir, a Full-Stack Developer with 6+ years of experience in web applications and financial analysis. I understand that creating a comprehensive platform with features like a Market Sentiment Engine and Trade Opportunity Engine is crucial for your project. 1. First, I will design the frontend using Flutter Web to ensure a responsive and user-friendly experience for the dashboard. 2. Then, I will implement the backend using Python FastAPI, which will handle data processing and integrate various financial metrics and indicators you specified. 3. After that, I will set up a PostgreSQL database to store and manage all the financial data, ensuring smooth retrieval for analysis. 4. Next, I will develop the Market Sentiment and Risk Score Engines to provide users with actionable insights. 5. Finally, I will test the entire system rigorously to ensure accuracy and reliability before deployment. Even if you are not sure yet, I would be happy to provide a FREE detailed quotation and project proposal with a suggested roadmap at no cost. If you decide to work with someone else, you can still use my proposal as a solid reference document. >>> My Work: https://www.freelancer.com/u/mubashir021/Data-Analyst-30537935 <<< Drop me a message and let's get this sorted. Mubashir

@MKCHAND

Hi, see my work first then award your valuable project to me. You can see demonstration of my trading automation solutions. I am the master of trading automation. I can easily make your desired platform. I am senior Algo Trading Developer. Let’s discuss further details on chat.

@sanddep5

With an arsenal of skills that include Data Analysis, PostgreSQL, Python, and Web Development, I am confident that I can architect a robust and efficient solution for your market intelligence dashboard. I have a track record of transforming ideas into powerful, scalable digital products that produce real results. As you mentioned that the focus is on analytics in Phase 1 without direct buy/sell recommendations, my experience in creating data-driven insights will be especially valuable in this context. In terms of technology preference, I can readily match your requests for Flutter Web and Python FastAPI on top of a PostgreSQL database. My proficiency in these technologies will ensure that the backend is secure, responsive, and capable of handling large amounts of data efficiently. With regards to data analysis, I can handle intricate tasks such as creating VWAP or EMA Indicators and collecting diverse market data like NIFTY or India VIX.

@indreshpnk

Hello, I understand you need an AI-powered market intelligence dashboard for NIFTY, BankNifty, and Sensex that aggregates market, options, and global data to generate sentiment, risk, and trade opportunity signals. The goal is to build a structured analytics platform using FastAPI, PostgreSQL, and a Flutter Web frontend with real-time insights and scoring engines. Here’s what I can provide: • Backend development using Python FastAPI with modular services for market data ingestion, indicators (RSI, VWAP, EMA, PCR), and sentiment/risk scoring engines. • Data pipeline for equities, options chain, OI, VIX, and global indices with structured PostgreSQL storage and optimized query design. I bring over 4+ years of experience in Python, FastAPI, financial data systems, API integration, data analysis, and full-stack dashboard development. I have worked on analytics platforms, real-time data processing systems, and trading-related dashboards with a focus on performance, scalability, and clean architecture. Just to clarify a few things: • Which market data source/API are you planning to use for NIFTY, options chain, and global indices (e.g., NSE API, paid feeds, or third-party providers)? • Do you want Phase 1 to include real-time streaming updates, or is periodic refresh (e.g., 1–5 min intervals) sufficient? Please come to the chat box to discuss more about your project. Best regards Indresh Kushwaha