Agentic AI development

@ZohaibRoy

⭐⭐⭐⭐⭐ Create an AI Agent to Write and Analyze Documents Efficiently ❇️ Hi My Friend, I hope you're doing well. I've reviewed your project requirements and noticed you're looking for an AI agent that can write documents based on prompts and gather information from the internet. Look no further; Zohaib is here to help you! My team has successfully completed 50+ similar projects in AI development. I will build a robust agent that can navigate web pages, download useful data, and analyze documents effectively. ➡️ Why Me? I can easily develop your AI agent as I have 5 years of experience in AI and automation, specializing in natural language processing, web scraping, and data analysis. My expertise includes creating efficient algorithms and building tools for data extraction. I also have a strong grip on machine learning frameworks, ensuring a comprehensive approach to your project. ➡️ Let's have a quick chat to discuss your project in detail, and I can show you samples of my previous work. Looking forward to discussing this with you in chat. ➡️ Skills & Experience: ✅ AI Development ✅ Natural Language Processing ✅ Web Scraping ✅ Data Analysis ✅ Python Programming ✅ Machine Learning ✅ API Integration ✅ Document Automation ✅ Data Extraction Tools ✅ Script Optimization ✅ Data Manipulation ✅ Agile Methodologies Waiting for your response! Best Regards, Zohaib

@irsolutions

With over 10 years of experience in web and mobile development, including expertise in AI/ML solutions, I understand the importance of developing and deploying an Agentic AI system that can effectively generate documents based on given documents and prompts. The ability for the agent to acquire information from the internet and analyze data/documents autonomously is crucial for the success of your project. In the realm of AI development, I have successfully implemented intelligent, data-driven features in various projects, ensuring enhanced user experiences. My experience aligns perfectly with the requirements of developing an Agentic AI system, and I am confident in my ability to deliver exceptional results for your project. I invite you to connect with me to discuss the details of your project further and explore how we can work together to bring your Agentic AI development goals to life. Let's collaborate and create a cutting-edge solution that meets your needs and exceeds your expectations.

@stevegtdbz

Hello! I have experience in tool development. Can provide a web vased solution using MEAN stack or a cli tool using python. Please open a chat to discuss further, thanks!

@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

@arzoof1

Hello I design and deploy production-ready agentic AI systems that go beyond simple prompt chaining—using Python, LangChain/LangGraph, OpenAI/Anthropic APIs, RAG pipelines, vector databases (FAISS/Pinecone), and tool-using agents with browser automation (Playwright) and custom tool execution to fetch, analyze, and synthesize live web data into structured documents. I can architect an autonomous agent that retrieves online sources, builds its own analysis tools, validates outputs, and generates high-quality documents with controlled reasoning and memory. I would be excited to discuss your exact use case and deliver a scalable, secure solution that exceeds your expectations. Best Regards, Arzoo Farooq

@OutsourceMan

⭐⭐⭐⭐⭐ We at CnELIndia, led by Raman Ladhani, have extensive experience developing AI-driven agents using Python, LangChain, and RAG frameworks. We can design an agent that ingests provided documents, integrates internet-based data acquisition via web scraping, and applies custom or existing analytical tools to process and summarize information effectively. Our expertise in GPT agents, vector databases, and prompt engineering ensures high-quality, context-aware document generation. We follow a structured approach: (1) requirement analysis and tech stack finalization, (2) agent architecture and tool integration, (3) implementation of retrieval-augmented generation, (4) iterative testing with real data, and (5) deployment with monitoring for continuous improvement, ensuring your AI agent meets performance and reliability expectations.

@kamran2012

Hi, I will build and deploy your agentic AI system that generates documents from reference materials and prompts, browses web pages to gather information, downloads relevant data, and writes or uses custom tools for data analysis. For the tool-use architecture, I will implement a ReAct-style agent loop where the LLM plans each step, selects the right tool (web browser, file reader, data analyzer), executes it, and evaluates the result before deciding the next action. This gives the agent reliable multi-step reasoning instead of single-shot output. Questions: 1) What LLM provider do you want as the backbone - OpenAI, Claude, or an open-source model you host yourself? 2) What types of documents should the agent produce - Word, PDF, Markdown, or another format? 3) Where will this be deployed - your own server, or a cloud platform? Send me a message and we can go over the details. Best regards, Kamran

@usamae

For this I'd go with a LangGraph or CrewAI-based agent architecture - both handle multi-step reasoning and tool use cleanly. The agent would have a few core tools: a web browser tool (Playwright headless for actual page rendering and JS-heavy sites), a search tool, a PDF/document reader, and a code execution sandbox for running analysis scripts it writes itself. For document writing based on gathered info, I'd set it up with a structured output pipeline - the agent gathers and summarizes, then a final generation step compiles it into a formatted document (Word/PDF via python-docx or reportlab). The "write its own tool" requirement is interesting - I'd handle that with a code-gen-and-exec loop where the agent can write Python, test it in a sandboxed environment, and then add it to its available tools for the session. Tools get saved and reused across runs. Quote depends on the scope - how complex are the workflows, how many document types, and what's the deployment target (local app, API, web UI)? Happy to discuss on a call. I also noticed your Hotel RMS migration project - I bid on that one too, if you want one person handling multiple things. - Usama

@techsty2014

Hello, I'm excited about the opportunity to develop an agentic AI capable of generating documents from provided inputs while acquiring web-based information and analyzing data. With my experience in AI development, I can create a robust agent using Python, TensorFlow, and NLP libraries like SpaCy or GPT. The AI will autonomously navigate web pages, extract relevant data, and apply analytical tools, potentially even writing custom scripts for unique tasks. Having previously developed AI solutions with similar requirements, I understand the importance of a reliable tech stack and efficient data handling. I can ensure the agent is both secure and scalable, adapting to various data sources and formats. Questions: • Is there a specific API preferred for web scraping, or should the agent develop tools as needed? • Are there particular document formats or outputs required beyond standard text files? Looking forward to collaborating on this innovative project to streamline document generation through AI. Thanks and best regards, Faizan

@Specgi

Having worked extensively in the Artificial Intelligence field, I strongly believe that my skills, experience, and passion for innovative problem-solving make me the perfect fit for your Agentic AI Development project. My hands-on experience in Google Cloud Vision and data analytics has equipped me with a deep understanding of not only the technology required for this task but also its potential applications. This includes abilities such as mining relevant data from websites, analyzing large datasets in real-time and making informed decisions based on them. Moreover, my proficiency in Python - coupled with my experience working with key technologies like TensorFlow and OpenCV - enables me to build robust AI models capable of processing complex documents. Throughout my career, I have demonstrated time and again the ability to develop machine learning solutions proficient not just in extraction of information from given text but also by combing through vast troves of unstructured data to retrieve information from online sources, conduct sentiment analysis or even factor in insights from social media.

@vishal1145

Your agent will fail if it cannot distinguish between hallucinated data and verified sources during web scraping. I've seen RAG systems confidently cite non-existent statistics because the retrieval layer wasn't filtering for source credibility. Before architecting this, I need clarity on two things: What's your tolerance for incorrect information in generated documents - are we talking internal reports where 95% accuracy works, or regulatory filings where one wrong number creates legal liability? And when you say "write its own tools," do you need the agent to generate Python scripts on the fly, or are we talking about chaining pre-built functions through LangChain? Here's the architectural approach: - LANGCHAIN + FUNCTION CALLING: Build a multi-agent system where one agent scrapes, another validates sources against a whitelist, and a third synthesizes documents. This prevents garbage data from polluting your outputs. - VECTOR DATABASES (Pinecone/Weaviate): Implement hybrid search combining dense embeddings and keyword matching so the agent retrieves contextually relevant chunks, not just semantically similar noise. - WEB SCRAPING + PLAYWRIGHT: Use headless browsers to handle JavaScript-rendered content and implement rate limiting to avoid IP bans. I'll add retry logic for flaky connections. - RAG WITH CITATION TRACKING: Every generated sentence gets tagged with source URLs and confidence scores so you can audit where information came from. - TOOL GENERATION: Use GPT-4's code interpreter mode to let the agent write pandas scripts for data analysis, then sandbox execution to prevent security risks. I've built 4 production RAG systems that process 50K+ documents daily. Let's schedule a 20-minute call to walk through your document types and accuracy requirements before I scope the full build.

@chiragardeshna

Hi there, I am a strong fit for this project because I have built agentic AI systems that combine document generation, web browsing, and tool-using reasoning in production environments. I have implemented LLM-driven agents using frameworks such as LangChain and LangGraph, integrated browser automation for web data extraction, built custom analysis tools in Python, and deployed secure backends with task orchestration. I would use a Python stack with FastAPI, a structured agent framework, a retrieval layer for document grounding, controlled web browsing via Playwright, and a tool-execution sandbox for safe data analysis. I reduce risk by isolating browsing and tool execution from the core model, implementing logging and audit trails, controlling prompt injection risks, and deploying the agent within a secure, containerized environment. I am ready to outline a concrete architecture, recommended model stack, and deployment plan based on your infrastructure. Regards Chirag

@AlexDeveloper911

Hi, We went through your project description and it seems like our team is a great fit for this job. We are an expert team which have many years of experience on Python, Web Scraping, Artificial Intelligence, Prompt Engineering, GPT Agent, LangChain, AI Agents, Vector Databases, Retrieval-Augmented Generation (RAG) Lets connect in chat so that We discuss further. Thank You

@PinnacleDigitalS

✅ Hello I'm so interested in your agentic development project! If you want results, clarity, and a little less stress, I’m your person. I communicate clearly, hit deadlines, and don’t disappear halfway through the project (rare skill, I know). Looking forward to your response. Best regards

@vanhuy19892011

Hi, I develop production-grade agentic AI systems using LLM orchestration frameworks and tool-enabled architectures. I can build an agent that writes structured documents from source files + prompts, browses the web, extracts data, and uses custom tools for analysis. Proposed stack: • Python + FastAPI backend • OpenAI / Claude models via API • LangGraph or CrewAI for agent orchestration • Browser automation (Playwright) for web access • Retrieval system (FAISS / pgvector) for document grounding • Tool layer for data parsing, summarization, structured outputs • Docker deployment (AWS/GCP) The agent will support document ingestion, web retrieval, tool execution, and controlled output formatting with guardrails. I’ve built similar multi-tool AI systems with browsing + RAG pipelines. Ready to discuss scope and deployment timeline. Best Regards.

@nin1

With expertise in AI and web data extraction, I can create an Agentic AI that effectively synthesizes documents. Leveraging Python and NLP frameworks, I'll ensure comprehensive data analysis. Let's discuss optimizing your AI for real-world applications!

@zu02

Dear Hiring Team, I can deliver a robust agentic AI that generates documents from prompts and source files, acquires information from the web, and analyzes data with custom or existing tools. My approach combines Python with LangChain, GPT agents, Retrieval‑Augmented Generation (RAG), and vector databases (FAISS/Weaviate). For web data acquisition, I use proven scraping libraries (Requests, BeautifulSoup, Playwright). The agent will: • Ingest documents and prompts, producing structured outputs. • Browse and scrape webpages to collect relevant data. • Implement a RAG pipeline for contextual retrieval. • Provide modular toolsets for analysis, extensible for future needs. Timeline: 7 days for initial delivery, including testing and refinements. Price: $2,250 USD (within your $1,500–$3,000 budget). Delivery: Milestone‑based updates with working demos at each stage. If you have preferred deployment environments (local vs. cloud) or specific document formats, I’d be glad to clarify. My goal is to deliver a reliable, extensible agent that meets your requirements and scales with future needs. Best regards, Zurab Esartia Zurab Esartia

@QuickMentor

Agentic AI development I'm excited after reviewing your project details! With over 5 years of hands-on experience in Web and App Development, I specialize in building high-performing, user-friendly, and fully responsive digital solutions tailored to your business needs. I hold an academic background in Computer Science and have successfully delivered numerous projects across various industries. My expertise includes: Custom Website Development (React, Angular, Laravel, PHP, WordPress, etc.) Mobile App Development (iOS, Android, Flutter, React Native) E-commerce & CMS Solutions (Shopify, WooCommerce, Magento) API Integration & Backend Development UI/UX Design & Prototyping Bug Fixing, Speed Optimization & Maintenance ✔ Clean, Scalable & Secure Code ✔ 100% Mobile & SEO-Friendly ✔ Ongoing Support & Unlimited Revisions Let’s turn your idea into a powerful digital product that exceeds expectations! Check my profile: https://www.freelancer.com/u/QuickMentor Looking forward to working with you!

@ivicab6

Hi, I’ve built agent-style LLM workflows that draft docs from source files plus prompts, with tool use for web research, downloading references, and running analysis before writing. Typical stack is Python with FastAPI, LangGraph (or LangChain), Playwright for safe webpage visiting, a sandboxed tool runner, and Postgres + pgvector for retrieval, shipped in Docker with basic monitoring. I can set up guardrails so citations and fetched files are traceable. If you want, we can start with one end-to-end agent that produces a single document type as a paid trial. Best Regards, Ivica