AI-Driven B2B Intelligence Platform Development

@avinashdubeyg209

Recently developed large-scale document intelligence solutions with FastAPI and asyncio, focusing on multilingual extraction. Can implement AI-assisted extraction pipelines and scalable AWS infrastructure to handle 50+ data sources efficiently. Expect validation from my tested, maintainable code integrated with real-time alerts. Ready to sign NDA to explore architecture and business logic further.

@vishal1145

Your crawling architecture will collapse under load if you're planning to hit 50+ sites simultaneously without distributed task queuing and exponential backoff. Most government portals in India throttle aggressively, and without proper session rotation, you'll get IP-banned within hours. Before architecting the pipeline, I need clarity on two things: What's your expected document ingestion rate during peak hours - are we talking 1K PDFs per day or 50K? This determines whether we need horizontal scaling with SQS + Lambda or a simpler ECS-based queue. Do your target websites require authentication or CAPTCHA handling? If you're scraping MCA or GST portals, we'll need headless browser pools with proxy rotation, which changes the infrastructure cost significantly. Here's the architectural approach: - PLAYWRIGHT + CURL-CFFI: Build a hybrid crawler that uses curl-cffi for static pages and Playwright only for JS-heavy sites, reducing compute costs by 60% while maintaining reliability. - POSTGRESQL + PGVECTOR: Implement table partitioning by date and company ID to handle 10M+ document records without query degradation, plus vector indexes for semantic search under 100ms. - ANTHROPIC CLAUDE + OPENAI: Set up a cascading LLM pipeline where Claude handles Hindi/Marathi extraction (better multilingual performance) and GPT-4 does structured validation, cutting API costs by 40% vs single-provider approach. - REDIS + SQS: Design a distributed task queue with priority lanes - urgent regulatory filings get processed in under 5 minutes while bulk historical data runs overnight to optimize Fargate costs. - TESSERACT 5 + PYMUPDF: Build an OCR fallback system that attempts native PDF text extraction first, only invoking Tesseract for scanned documents, reducing processing time from 8s to 400ms per page. - AWS ECS FARGATE + TERRAFORM: Deploy auto-scaling worker pools in ap-south-1 with spot instances for non-critical tasks, maintaining 99.9% uptime while keeping monthly AWS costs under $2K for 100K documents. I've built 3 similar intelligence platforms for fintech clients that process regulatory filings at scale. One handles 80K PDFs daily from SEBI and never missed an alert. Let's schedule a 20-minute technical call to walk through edge cases like partial PDF corruption and webhook retry logic before you commit to a build - I don't take on projects where failure scenarios aren't mapped upfront.

@kingxanda

Hey, Thanks for your post. I'v read your description carefully. I have relevant experience I can help. some of my skills are: JavaScript, Bots, Python, Nodejs, Webscraping, Apis Hope you're having a nice day my friend :)

@sonika1419

**DO NOT PAY ME UNTIL I COMPLETE! :)** Hello my valuable client :) My profile is new over here but I have 7 years of experience in this field. I have completely understood about your project. Also I will provide you free maintenance on your project for 1 year after project completion. I can definitely complete this in your timeframe. Give me one chance to prove myself. Hit the chat button to get started. If you will not like my work then you dont need to pay me any money so dont worry and have faith in me :) I am eagerly waiting for your message.

@himanshus642

With an in-depth understanding of both your project's technical requirements and wider business goals, I believe I'm uniquely qualified to take on the challenge of building your B2B intelligence platform. My five years of experience as a Full Stack Developer has seen me specialize in highly intricate, scalable, and intelligent systems. I am well versed in working with large-scale data acquisition processes, AI-powered extraction, search optimization, and multi-channel notifications. Handling AWS infrastructure (particularly in Mumbai region), from IAM to ECS Fargate and Secrets Manager, is one of my considerable strong suits. This encompasses creating robust PostgreSQL schemas with migrations and deploying AWS architectures through Terraform. My skill set also includes efficient usage of modern tools such as Playwright for web scraping, asyncio for asynchronous processing, FastAPI for production-grade APIs, among others. To top it off, I've experience using Tesseract 5 OCR engine for impressive PDF processing performances. Being an important component of this long-term project requires strict adherence to secure and reliable coding practices, stringent testing methodology around high-load scenarios (10k+ documents/day), and maintaining comprehensive monitoring frameworks. On all counts I can provide exactly what you need at different stages of the project lifecycle. Let's get started on this exciting venture that aligns so well with my skills today!

@seandinwiddie

Hi, there, I can help architect and build your production-grade B2B intelligence platform with scalable crawling, multilingual document processing, AI-powered extraction, semantic search, and enterprise-grade AWS deployment. I have strong experience with Python/FastAPI ecosystems, distributed processing, PostgreSQL optimization, OCR pipelines, LLM integrations, Dockerized microservices, and cloud-native infrastructure. The platform will be designed for reliability, observability, and long-term scalability using ECS Fargate, Redis queues, pgvector/OpenSearch, structured extraction pipelines, and robust CI/CD workflows. I can also help implement multilingual OCR flows, risk scoring engines, hybrid search, alert systems, and AI-assisted reporting while maintaining clean architecture and production-quality testing standards. I’m comfortable working under NDA, collaborating in IST-friendly hours, and supporting long-term product evolution with milestone-based or retainer engagement models. Let’s discuss your architecture goals, scaling expectations, and deployment strategy in detail. Best Regards, Sean D.

@souvikbasu

Hi, I'm a Python and AI developer who's built end-to-end data pipelines combining web crawling, OCR, and LLM-powered extraction. When I read your spec — distributed crawler for 50+ sites, multilingual OCR across Hindi/Marathi/English, semantic search, and real-time alerting — this is exactly the kind of system I work on. My approach: • Scrapy/Playwright for distributed crawling with anti-bot handling • Tesseract + IndicNLP for Indic-language OCR + NER extraction • LangChain + GPT-4 for structured field extraction and AI report generation • Elasticsearch for hybrid semantic + keyword search • FastAPI backend, Celery + Redis for async pipeline orchestration • AWS ECS/Fargate + Terraform for infra-as-code, Airflow for scheduling • OpenTelemetry + Grafana for observability I've worked on high-volume document pipelines and understand where Indic OCR degrades on scanned PDFs — and how to handle that gracefully in a cascade fallback strategy. Happy to walk through the full architecture within 48 hours of kickoff.

@indreshpnk

Hello, I understand you need a production-grade B2B Intelligence Platform with distributed web crawling, multilingual OCR-based document processing, AI-driven structured extraction, semantic search, risk scoring, and real-time alerting deployed on AWS (Mumbai region). The goal is a scalable, compliant, enterprise-level intelligence system. Here’s what I can provide: • Distributed crawler + queue-based ingestion system using Playwright/httpx for 50+ sources • AI-powered extraction pipeline with OCR (Hindi/Marathi/English) using Claude/OpenAI with structured JSON outputs • Hybrid intelligence layer with pgvector/OpenSearch for semantic search, risk scoring, and alerting engine I bring over 4+ years of experience in Python, FastAPI, AWS, and building large-scale distributed data pipelines with AI/LLM integration, focusing on performance, scalability, and clean production-grade architecture. Just to clarify a few things: • What is your expected daily document ingestion volume and latency requirement? • Do you already have predefined extraction schemas or should we design them from scratch? Please come to the chat box to discuss more about your project. Best regards Indresh Kushwaha

@aprkdream

I understand that you're building a production-grade B2B intelligence platform, leveraging AI to extract insights from public data and multilingual documents. I'll focus on developing the backend infrastructure, utilizing my expertise in Node.js, Laravel, and complex systems to ensure seamless data ingestion, processing, and analysis. With experience in integrating third-party APIs, including AI-powered services, I'll design an architecture that efficiently extracts structured intelligence and delivers actionable insights. I've worked on similar projects, developing scalable systems for ERP and CRM platforms, and integrating payment gateways like Stripe and Razorpay. For this project, I'll deliver a robust backend system that meets your requirements, including large-volume document ingestion, AI-assisted extraction pipelines, and search functionality. I'll also ensure the system is well-documented, maintainable, and scalable for future growth. As a seasoned developer, I'll provide clear communication and collaboration to ensure the platform meets your business needs. I can deliver this in 7 days.

@ammarahmed20

As an experienced Full Stack Developer for over 6 years, I specialize in building scalable web applications, SaaS platforms and AI-powered systems - precisely the kind of expertise you need for this long-term engagement. I am comfortable working with high-scale architectures similar to yours, designed for document intelligence, enterprise-grade observability and scalable AWS infrastructure. My proficiency with Python 3.11, FastAPI, asyncio, and other backend tools naturally blends with my knowledge of document processing and OCR using pdfplumber, PyMuPDF and Tesseract. Not only can I handle large-volume document ingestion but also develop a suite of microservices for effective extraction pipelines using OpenAI API and Anthropic Claude API. Being fully versed in PostgreSQL and experienced in designing search infrastructure with OpenSearch / Elasticsearch, I can ensure efficient data storage, query optimization and retrieval using JSONB and custom analyzers. Moreover, I have working knowledge in Redis for implementing queues, caching and throttling functionalities. Lastly, keeping in mind your preferred engagement model of fixed-price or milestone-based delivery, my approach prioritizes clean execution of projects enveloped in thorough plans. My code is reliable, scalable, well-documented and strictly follows your time-zone constraints for seamless coordination. Let's join hands to build an exemplary B2B intelligence platform!

@Serg2024

Hello, I’m very interested in your B2B intelligence platform project. The scope aligns strongly with my experience in Python backend development, data pipelines, AI integrations, and scalable cloud-based systems. I have experience working with: • Python, FastAPI, asyncio, PostgreSQL • Web crawling and automated data extraction • OCR/document processing workflows • OpenAI API integrations and structured AI extraction • Dockerized services and cloud deployments • Data processing, analytics, and automation pipelines Your architecture requirements around distributed crawling, multilingual document intelligence, hybrid search, and scalable AWS infrastructure are especially interesting to me. I understand the importance of production-quality engineering, observability, maintainability, and long-term scalability for systems handling large document volumes and real-time intelligence workflows. I’m comfortable working with milestone-based or long-term engagement models and can support ongoing product evolution after launch. I would be happy to discuss: • architecture approach • deployment strategy • delivery milestones • long-term support • NDA execution and next steps Looking forward to learning more about the platform. Best regards, Sergey

@ArasakaSystems

Your biggest risk here probably isn’t development complexity—it’s maintaining data integrity and operational reliability at scale with diverse Indian-language sources and strict compliance needs. Building a loosely coupled, observable pipeline that treats each stage—crawling, OCR, AI extraction, search—as an independently scalable service prevents bottlenecks and ensures fault isolation. Prioritizing typed, tested code and AWS-native metrics early avoids tech debt and supports smooth long-term evolution. Leveraging queue orchestration with async Python and ECS Fargate fits your Mumbai-region constraints while enabling high throughput and cost control. Let’s explore how I’d align architecture to your product’s true growth levers.

@zarrukhr

Hello, We have experience building production-grade AI/data platforms focused on large-scale ingestion, OCR/LLM extraction, and AWS infrastructure. Your requirements align closely with our stack and engineering approach. Core expertise: Python 3.11, FastAPI, asyncio Distributed crawling with Playwright/httpx/curl-cffi OCR pipelines using PyMuPDF, pdfplumber, Tesseract Multilingual document extraction (including Indic-language workflows) OpenAI/Claude integrations with structured JSON extraction PostgreSQL, pgvector, OpenSearch, Redis AWS ECS Fargate, Terraform, CI/CD, Docker Observability with Sentry, OpenTelemetry, Grafana We’ve built scalable backend systems handling high-volume async processing, queue orchestration, retry/rate-limiting logic, and AI-powered search/reporting workflows. Our approach: Event-driven microservice architecture Async worker pipelines S3-based document storage Hybrid semantic + keyword search Schema-validated extraction with confidence scoring Fully containerized AWS deployment in ap-south-1 We prioritize maintainability, testing, observability, and long-term scalability from the start. We’re comfortable with NDA execution and can support both milestone-based delivery and long-term post-launch maintenance. Happy to discuss architecture, timelines, and relevant production experience after NDA.

@akhileshr108

Hello, Your project aligns strongly with my experience in FastAPI backend systems, AI pipelines, scalable APIs, Docker, AWS deployment, and ML-driven data processing. I am a Software Developer & AI Engineer from Nagpur with hands-on experience building production-oriented systems using Python, FastAPI, PostgreSQL, Docker, AWS, MLflow, CI/CD, and scalable ML workflows. Relevant work includes: • F1 Prediction & Ranking Platform using FastAPI, XGBoost, Docker, AWS, GitHub Actions, and MLflow • Automated Market Intelligence & Forecasting Pipeline with TensorFlow, Scikit-Learn, feature engineering, and large-scale automated processing • Cloud-native APIs and scalable backend systems I am comfortable with: • FastAPI + asyncio architectures • PostgreSQL + JSONB • Dockerised microservices • Redis pipelines • OpenAI integrations • OCR/document workflows • AWS infrastructure & deployment • Typed, maintainable, production-grade code What interests me most is the distributed systems and AI-document intelligence aspect of your platform. Since we are both from Nagpur, communication and collaboration will also be smoother. Open to milestone-based or long-term engagement. Looking forward to discussing the architecture and execution approach. Regards, Akhilesh Raut

@guptakishan805

As an experienced technology partner, I offer you more than just coding expertise. My approach aligns perfectly with your long-term product engagement requirements, from Discovery to MVP and Scale; I'm all about planning, building, and evolving robust platforms for startup success. With in-depth knowledge of AI Development, Backend Development, OpenAI, PostgreSQL, and Python; I am ready to meet every requirement of your B2B intelligence platform. In particular, my experience with Web Crawling and Data Acquisition is something that really fits this project's demand for scraping data from 50+ websites. Alongside that, my expertise in handling large volumes of data ingestion and working with AI-assisted extraction pipelines will greatly benefit your production-grade architecture goals. Additionally, my competency with Elasticsearch and Redis will help me in boosting proficient search capabilities and ensuring efficiency in task queuing for rapid real-time business alerts. Lastly, one of my biggest facets in the tech world is ensuring vigilant observability throughout the system to tackle any impending bugs or failures smartly. I am well-versed with tools like Sentry and OpenTelemetry; this would immensely contribute to setting up an impeccable operational tooling & monitoring regime for you. Let me assure you that if given the opportunity to serve on this project, my dedication for producing maintainable code while rising up to any compliance requirement will be unmatched.

@samarthhsingh

Hi, I architect high-throughput data ingestion pipelines and reliable scraping systems. The architecture direction for this project directly aligns with the structured extraction and operational workflows I build for production environments. I have engineered backend pipelines that handles my daily research workload, ensuring robust API integration and maintainable search system architectures. My focus is strictly on scalable operational automation and bypassing extraction barriers. I am ready to execute the NDA. Let us review your current ingestion flow and infrastructure stack so we can map out the specific backend requirements to scale your platform. Best, Samarth

@sayantandey007

Hello, I have almost 2 years of experience in Computer Vision and Generative AI field. I have skilled in python, fastapi, multiprocessing, multithreading, web scraping and crawling using playwright,httpx,curl-cffi. I have knowledge about databaases like supabase, MySQL, agentic frameworks like langchian, langgraph. I have also experienced with Railway Platform for deployment. I have a team of 4 members with same experience. We will be good fit for this project.

@prakhark43

Hi there, I’ve reviewed the requirements for your production-grade B2B intelligence platform. Given the focus on large-scale data acquisition, multilingual document processing, and high-scale architecture, I am confident in delivering a robust, long-term solution. Relevant Experience & Approach:- *AI-Driven Systems: Extensive experience building backend architectures and AI-driven systems, specifically utilizing RAG (Retrieval-Augmented Generation) pipelines. *Production Python:Professional background in Python development focused on maintainable, production-ready codebases. *Data & Search: Implementing PostgreSQL 14+ with pgvector for semantic search and OpenSearch with custom analyzers for multilingual support (English, Hindi, Marathi). *Scalable Pipeline: Using Redis for high-performance queuing across 50+ crawler sources and Apache Airflow for complex workflow orchestration. * AWS Infrastructure:Deployment on ECS Fargate (Mumbai) using Terraform for IaC and GitHub Actions for full CI/CD. Engagement Strategy: *Team Lead: I operate as a lead developer focused on backend architecture and AI integration, capable of working independently to support long-term product evolution. *Execution: A phased rollout starting with core ingestion, followed by AI extraction and real-time alerts. Ready to sign the NDA for further technical discussion. Best regards, Prakhar Katiyar

@aitec3

Hi, I am an AI/ML Engineer with 3+ years of experience in Generative AI, NLP, LLMs, OCR, Computer Vision, and scalable backend development. I have worked on AI-powered automation systems, RAG-based chatbots, document intelligence platforms, and HR automation solutions using Python, FastAPI, LangChain, OpenAI, and PostgreSQL. I have experience with: • AI/LLM application development • OCR and document extraction pipelines • RAG and semantic search systems • FastAPI backend APIs and async processing • Docker, AWS, Kubernetes, and MLOps workflows Recently, I worked on: • HR Automation & AI Candidate Hiring System • PDF Q&A Chatbot using RAG and Llama3 • AI-powered document extraction and summarization pipelines I can deliver scalable, production-ready solutions with clean architecture and efficient workflows. I am comfortable with long-term collaboration, NDA agreements, and IST timezone communication. Hourly Rate: $4–8/hour Looking forward to working with you. Best regards, Pradnya Patare