lex-rfp

Generative AI-powered RFP and proposal automation for LegionIO. Ingests past proposals and product documentation into Apollo, generates draft RFP responses via the LLM pipeline with RAG retrieval, provides human-in-the-loop review workflows, and tracks win rates with quality analytics.

Monolith-style extension with four sub-modules:

gem install lex-rfp

Or add to your Gemfile:

gem 'lex-rfp'

Each sub-module provides a standalone Client class:

# Ingest documents
ingest = Legion::Extensions::Rfp::Ingest::Client.new
result = ingest.ingest_document(file_path: 'past_proposal.pdf', tags: ['healthcare'])
chunks = result[:result]

# Generate RFP responses
gen = Legion::Extensions::Rfp::Generate::Client.new
draft = gen.generate_response(question: 'Describe your network coverage')

# Review workflow
review = Legion::Extensions::Rfp::Review::Client.new
wf = review.create_workflow(proposal_id: 'prop-123', sections: %w[summary approach pricing])
review.submit_for_review(workflow_id: wf[:result][:id], reviewers: ['reviewer-1'])

# Analytics
analytics = Legion::Extensions::Rfp::Analytics::Client.new
rate = analytics.overall_win_rate(proposals: proposal_data)

• supported?(file_path:) - Check if a file format is supported
• extract_text(file_path:) - Extract text from a document
• chunk_text(text:, chunk_size:, overlap:) - Split text into overlapping chunks
• ingest_document(file_path:, tags:, metadata:) - Full document ingest pipeline
• ingest_directory(directory:, tags:, recursive:) - Batch ingest all supported files
• ingest_to_apollo(chunks:, scope:) - Push chunks to Apollo knowledge store
• parse_rfp_questions(text:) - Extract numbered questions from RFP text
• extract_requirements(text:) - Identify mandatory and preferred requirements
• extract_sections(text:) - Split RFP into logical sections

• generate_full_draft(rfp_text:, context:, model:) - Generate complete RFP response
• generate_response(question:, context:, model:, scope:) - Generate single question response with RAG
• regenerate(question:, previous_answer:, feedback:) - Revise response based on feedback
• generate_section_response(question:, section:, context:) - Section-specific response
• generate_executive_summary(rfp_text:, company_context:) - Executive summary generation
• generate_compliance_matrix(requirements:, capabilities:) - Compliance matrix
• list_templates / get_template(name:) / apply_template(name:, rfp_data:) - Template management
• suggest_template(rfp_text:) - Auto-suggest appropriate template

• create_workflow(proposal_id:, sections:, reviewers:) - Create review workflow
• update_status(workflow_id:, status:) / update_section_status(...) - Status management
• submit_for_review(workflow_id:, reviewers:) - Submit for review
• finalize(workflow_id:) - Finalize proposal
• add_comment(...) / resolve_comment(...) / request_revision(...) - Comment system
• approve_section(...) / reject_section(...) / approve_proposal(...) - Approvals
• check_readiness(sections:) - Check if all sections are approved

• record_proposal(proposal_id:, rfp_source:, ...) - Record proposal metadata
• record_outcome(proposal_id:, outcome:, revenue:) - Record win/loss outcome
• summary(proposals:) - Aggregate statistics
• response_time_stats(proposals:) - Response time analysis
• overall_win_rate(proposals:) - Overall win rate
• win_rate_by_source(proposals:) / win_rate_by_template(proposals:) - Segmented rates
• trend(proposals:, period:) - Win rate trends over time
• score_response(response_text:, question:, requirements:) - Quality scoring
• score_proposal(sections:) - Full proposal quality score
• quality_report(proposals:) - Aggregate quality report

• PDF (via legion-data Extract)
• DOCX (via legion-data Extract)
• Markdown (.md, .markdown)
• Excel (.xlsx, via legion-data Extract)
• HTML (.html, .htm)

• Ruby >= 3.4
• LegionIO framework
• faraday (>= 2.0)
• Optional: legion-llm for LLM-powered generation
• Optional: legion-apollo for RAG retrieval
• Optional: legion-data for PDF/DOCX/Excel extraction

MIT