Excel-Claude Integration Script

@arifshaon

Hello, I would build this as a small, reliable Python command-line tool rather than an overcomplicated system. I would use openpyxl or pandas for reading and writing Excel, and requests for direct Claude API calls. The script would work row by row: read the company name and any related input fields, generate a controlled Claude prompt using your required JSON schema, then validate the response before writing anything to the output workbook. I would not treat the AI response as free text; I would parse it strictly as JSON and map each key to a dedicated Excel column. For companies with more than one contact, I would flatten the result so each contact becomes its own row while keeping the company-level details repeated consistently. I would also include a checkpoint file, so if the run stops midway, it can restart without reprocessing completed companies. To make it stable for batch work, I would add retry handling, exponential back-off for rate limits, configurable delays, and an error log for invalid JSON, empty results, or failed API calls. API keys would be loaded from environment variables, not hardcoded. I would deliver a fully commented Python script, a short setup guide, dependency instructions, and clear restart/retry steps. Full unrestricted code rights would be included.

@adriank06

Hi there, I have done several projects similar to your project. Two of these projects are: 1- For a drug marketing company, I developed an agentic AI pipeline that gets the name, ingredients and target disease of a newly developed drug, then, it search web using serpapi library to find the possible competitors. After that, another LLM agent look at the NIH drug database to find the competitors that are mostly prescribed by physicians in the US. After that, another agent sort the physicians based on their importance and finally output a json containing the physicians, their state, zipe code etc. 2- The other project was for a Building Stone Trading company in which, I developed an agentic pipeline to find possible customers in any target country or city of that country. The final output was the name of possible customers, and their contact infos. Considering the above, I'm confident I can build an agentic pipeline that: 1- first look at the contact info of the people in every company through web search. 2- Then, it give the results to Cluade API to extract the people and their contacts and put it in the json structure that you want. 3- Finally, it outputs an excel file containing all companies, people and the contact info. To handle errors, I will also save the row line so, the agent will start from that line again. I also do a error handling to prevent any stop during the process and finallt print number of rows that have been succefully processed. The libraries that I will use are: 1- Anthropic for Cluade API connection 2- LangGraph for agentic AI development 3- serpapi for web search 4- pandas I can assure you my suggested pipeline will work for this project. If my proposal fits to what you want please let me know so we can discuss the details furthur. Thanks, Adrian

@ttobio69

Hi there, I read your requirements carefully, and I can build a compact Python workflow that reads company names from Excel, sends each company to Claude through the official API, receives strict-format JSON, and writes the parsed contact data back into Excel row by row. My approach will be: Use Python 3.x with requests for Claude API calls Use pandas/openpyxl for Excel reading and writing Process each company name from the source sheet Parse returned JSON into explicit columns like name, title, email, phone, website, etc. Create separate rows when multiple contacts are returned for one company Add retry/back-off delays for rate limits Add error logging and resume support from the last processed row Store API keys securely using environment variables I’ll keep the script clean, fully commented, and easy to run without UI automation or copy-paste handling. Cost: ₹1,000/hour || Timeline: 1–2 days Payment and timeline details can be discussed further to align with your expectations. I’d be happy to deliver a reliable, well-structured script with full setup notes and unrestricted code ownership. Best regards, Oluwatobi Okedairo

@perfectwriter002

Hello client, I am excited to submit my proposal for your project. With years of experience in the field, I am confident in my ability to deliver high-quality work that meets your needs. I have carefully reviewed your project description and requirements; I understand that you are looking to achieve your project objectives. My approach will ensure that I deliver exactly what you have requested in the project. I will keep you updated on the project progress and ensure timely delivery. If you are interested in moving forward I’d be happy to discuss the project further and answer any questions you may have. Thanks for considering my proposal; I look forward to the opportunity to work with you. Please open your messenger and send me complete details to discuss it further. Thank you.

@ravikumarsingh1

This is a clean ETL-style workflow (Excel → Claude API → structured Excel), and I’ll build it to be reliable, resumable, and strictly schema-driven. Approach 1. Input Layer Read Excel via pandas Normalize company names + track row index for resume 2. Claude API Integration Use requests (no UI automation) Strict prompt enforcing JSON-only output (schema-locked) Validate response before processing 3. Parsing & Expansion Parse JSON → flatten contacts For multiple contacts: Create one row per contact Repeat company-level fields Map each JSON field → dedicated Excel column (no free text dumps) 4. Reliability Rate-limit handling: Exponential backoff + delays Error logging (failed rows saved separately) Resume mode: Continues from last successful row (checkpoint file) 5. Output Clean Excel via pandas/openpyxl Consistent column structure (predefined schema) Deliverables Fully commented Python script (.py) Setup guide: Dependencies API key config (env variables) Run + resume instructions Key Design Choices Stateless API calls (safe retries) Schema validation before write Modular functions (easy to extend fields later) I’ll make sure the script is robust for large batches and easy for you to run without babysitting. I can start immediately.

@oimrqs

I can build this API-only Python workflow cleanly. My approach: read the Excel input with openpyxl or pandas, call Claude through requests using an environment variable for the API key, enforce your strict JSON schema, validate malformed responses, and write one output row per returned contact while repeating the parent company data. I will also add retry/backoff, error logging, a checkpoint/resume switch, and a short setup/run guide. To start I would need your sample workbook, exact JSON schema, and one expected output example.

@tinyopsezr

Hello, TinyOps Studio can help with this as a small, testable automation build. For the first pass, I would keep the workflow narrow and reliable: - Confirm the trigger, inputs, success condition, and manual review point before building. - Keep the first slice small enough to test end-to-end with synthetic data. - Deliver importable workflow/config files plus a short runbook for setup and validation. Implementation style: readable n8n nodes, clear step names, validation for missing required fields, and visible notes when an external API/model step fails. For "Excel-Claude Integration Script", I would start with one useful workflow slice first, then repeat the pattern once the handoff format is approved. Bid: $750.0 hourly rate. No external contact details needed; Freelancer messages/files are enough for the first scoped pass.

@tejachary

Hi, Your requirement is clear, and I can build a compact, reliable Python workflow that reads company names from Excel, processes them through Claude’s API, and writes structured results back into Excel with one row per contact. ### ? Planned Approach **1. Input Handling (Excel → pandas)** I’ll read the company list using pandas with flexible column handling to keep it adaptable. **2. Claude API Integration (requests)** * Direct API calls (no UI automation) * Carefully designed prompt to enforce strict JSON output * Validation layer to ensure responses match your schema **3. JSON Parsing & Normalization** * Safely parse responses * Expand multiple contacts into separate rows * Preserve company-level data across all rows **4. Output (Excel Write-back)** * Structured output using pandas/openpyxl * Each field mapped to its own column exactly as defined **5. Reliability & Error Handling** * Exponential backoff to avoid rate limits * Logging for failed or malformed responses * Resume functionality to continue from last processed row --- ### ⚙️ Tech Stack Python 3.x, requests, pandas, openpyxl --- ### ? Deliverables * Fully commented Python script * JSON schema + Claude prompt template * Error logging + checkpoint system * Setup and usage guide --- I focus on clean, maintainable, and reliable code that works consistently at scale. You’ll have full ownership of the final solution. Looking forward to working with you. Best regards, Teja Chary