Overview

Responding to RFPs is often manual and fragmented. Proposal teams spend hours extracting formats, hunting for prior answers, and consolidating edits, all while jumping between tools and managing version control.

To solve this, Optimus developed AutoRFP, an AI-powered assistant that operates directly within Microsoft Teams to automate RFP response creation. From parsing the required response format to section-by-section drafting, review, and export, AutoRFP enables end-to-end proposal production through a conversational experience.

The Challenge

Proposal managers and SMEs faced recurring bottlenecks:

  • Manual formatting and structure: Extracting response templates from RFPs took time and introduced inconsistencies.
  • Scattered knowledge: Prior responses and approved language were difficult to reuse reliably.
  • Inefficient review cycles: Iterations across sections were ad hoc and hard to track.
  • Context switching: Teams moved between chats, documents, and repositories, slowing momentum.

The Solution

Optimus built AutoRFP, a Teams-native AI assistant that automates the RFP response lifecycle:

  • Parses the RFP to detect the required response format (sections and questions).
  • Generates a first draft per section using the organization’s approved materials.
  • Enables structured review: Approve, edit manually, or ask AI to revise, section by section.
  • Tracks progress until all sections are approved.
  • Exports a properly formatted Word (.docx) response for submission.

Result: A focused, conversational proposal workflow embedded where teams already collaborate.

Key Capabilities

  • Automated Format Extraction: Detects required sections and builds a consistent response outline.
  • Draft Generation: Creates section drafts using organization-approved content.
  • Guided Review Loop: Approve, edit, or regenerate with targeted feedback.
  • Structure and Styling: Applies consistent headings, numbering, and styles across sections.
  • Final Export: Produces a submission-ready .docx with the approved content.
  • Learning Over Time: Adapts to preferred phrasing, templates, and tone guidelines.

Multi Agent Architecture

Agent Name Role
AutoRFP Orchestrator Coordinates flow across all agents and manages conversation state
Document Ingestion Agent Processes uploaded RFPs and extracts required response structure
Format Extraction Agent Builds and updates the response format (sections, ordering, metadata)
Drafting Agent Generates first drafts using approved organizational materials
Feedback and Regeneration Agent Applies user feedback and regenerates until approved
Compliance and Styling Agent Enforces style, headings, and required boilerplate
Export Agent Assembles approved sections and produces the final .docx
Repository Integration Agent Reads approved source materials and writes finalized exports to the designated repository

Deployment

AutoRFP was rolled out in phases across proposal and sales teams.

  • Runs in Microsoft Teams, minimizing tool switching
  • Built with Microsoft Bot Framework and Azure Functions
  • Azure OpenAI (GPT-4o) for content generation
  • MSAL for secure authentication and consented access
  • GitHub Actions for CI/CD
  • Azure Monitor for performance, usage, and reliability tracking

The Results

  • Faster response assembly: Less time spent extracting formats and locating prior answers
  • Consistent structure and style: Standardized sections and formatting across proposals
  • Streamlined reviews: Clear per-section approvals and targeted revisions
  • Reduced context switching: Conversation, drafting, and export happen in Teams

Tangible Business Outcomes:

  • Accelerated Turnaround: Proposal teams move from intake to first draft significantly faster
  • Lower Coordination Overhead: Structured review reduces back-and-forth across tools
  • Improved Consistency: Reuse of approved language elevates quality and compliance
  • Higher Adoption: Familiar Teams interface encourages everyday use

Technologies Used

  • Microsoft Teams
  • Microsoft Bot Framework and Copilot Studio
  • Azure OpenAI (GPT-4o)
  • Azure Functions
  • MSAL Authentication
  • GitHub Actions (CI/CD)
  • Azure Monitor

What’s Next

  • Template Libraries: Pre-approved section templates by industry and deal type
  • Multilingual Drafting: Support for regional proposals and translations
  • Policy Guardrails: Inline checks for restricted claims and required disclosures
  • Smart Snippet Suggestions: Surface relevant past answers during drafting
  • Collaboration Views: Side-by-side section reviews and sign-off tracking

Contact Optimus to learn how we can help you leverage Agentic AI & Cloud services.

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