Happy to help here, or hit me up at sebgnotes@gmail.com
I'm thinking something like:
1. Extract and Parse the RFP
Use an LLM for summarization and section extraction.
Leverage OCR tools (e.g., Tesseract, AWS Textract, or Azure Form Recognizer) if the RFPs are PDFs with scanned text.
Convert the RFP into structured data using LangChain’s document loaders or Unstructured.io.
2. Automate Reusable Content Insertion
Maintain an answer bank (e.g., .txt, .md, Notion, Airtable, Google Docs, or even a vector database like Weaviate or Pinecone).
Implement retrieval-augmented generation (RAG) to pull relevant answers dynamically.
LlamaIndex or LangChain can help fetch the closest responses.
Use Embeddings (OpenAI, Cohere, or Ada models) for semantic search.
If a response needs tweaking, allow the AI to highlight differences and suggest edits.
3. Prompt for Missing Information
If the AI detects missing information:
Generate a draft response using context from existing data.
Provide a structured form/UI (e.g., Google Forms, Typeform, or an internal dashboard) for manual input.
4. Generate the Final RFP
Use LLMs to rewrite responses for coherence and consistency.
Automate formatting with Markdown-to-PDF tools (Pandoc, LaTeX) or Microsoft Word templates.
Consider using Zapier or Make.com to integrate responses into a shared document repository. Low-Code/No-Code Approach
If you want minimal coding:
Microsoft Copilot (Word + Excel) or Google Gemini AI could automate drafting and inserting responses.
Zapier + OpenAI + Google Docs can build a pipeline to parse, retrieve, and generate answers. Notion AI can assist in structured knowledge retrieval.
Would love to hear more about your constraints (e.g., compliance needs, integration with existing tools) to refine this further.
Given that, here’s a streamlined approach:
1. Extract RFP Content
Azure Form Recognizer, AWS Textract, or Adobe Acrobat API can extract text and structure from PDFs.
If RFPs follow a standard layout, LlamaIndex or LangChain can help chunk and categorize sections.
2. Retrieve and Insert Answers
Use Google Docs API to pull relevant responses based on keyword or semantic search.
OpenAI Assistants API or Claude 3 can rephrase and tailor the responses dynamically.
3. Automate Formatting with a Template
Microsoft Copilot (Word/Excel + SharePoint):
Copilot can fetch Google Doc answers and insert them into a predefined template.
If you standardize the output format in Word, you can generate a PDF-ready final draft.
Alternative: Python + Pandoc + Jinja2 templates if you want a more controlled workflow.
4. Output Final PDF
Convert the formatted document to PDF using Word’s built-in save-to-PDF, Pandoc, or LibreOffice headless mode.
** Low-Code Implementation
If you're looking for minimal coding:
Microsoft Power Automate + Copilot → Automatically extract, populate, and format RFP responses.
Zapier + OpenAI + Google Docs → Retrieve answers, format them, and push to a doc/PDF.
Would Copilot’s Word integration work within your workflow, or do you need more automation for final formatting?
If you want a completely hands-off approach, a small workflow automation script could eliminate the remaining 20% of manual work.