🎯 Goal
When a client releases a Request for Proposal (RFP) or Tender Document, they express technical requirements — but often, they also reveal deeper buying motivations, unspoken expectations, or concerns.
Outmind lets you launch an AI assistant that analyzes these documents and helps you identify:
Implicit expectations
Hidden concerns
Key decision drivers
— all inferred from tone, phrasing, and repetition.
🧠 How It Works
You select one or several documents from the RFP (e.g., specs, T&Cs, templates, annexes…) and ask the assistant:
“Can you analyze this RFP to detect implicit expectations and potential purchase blockers?”
The assistant will:
Read the full content
Cross-analyze language patterns using frameworks like SONCAS, rational buying criteria, ESG factors, and known friction points
Produce a structured report highlighting weak signals, repeated themes, and nuanced phrasing
🧩 What the AI Analyzes for You
🔍 Implicit Motivations (via SONCAS model)
Security: guarantees, certifications, service continuity
Pride: supplier reputation, prestige, recognition
Novelty: innovation, transformation, modern tools
Comfort: simplicity, turnkey service, support
Money: pricing pressure, ROI, TCO
Likeability: human touch, proximity, responsiveness
Sustainability: environmental expectations, CSR language
🧠 Rational Buying Criteria
Brand, price, technical quality, design, local presence, after-sales support, etc.
⚠️ Potential Purchase Barriers
Budget limits
Doubts about quality or fit
Complexity of offer
Perceived risk
Competitive comparisons
🌱 ESG Expectations (Environmental, Social, Governance)
CO₂ emissions, waste management, responsible materials
Inclusion, working conditions, local impact
Transparency, compliance, anti-corruption
📄 Output Generated by the Assistant
A concise report, with these sections:
✅ Implicit expectations (categorized by rational criteria)
⚠️ Identified blockers (with original text excerpts)
🌍 ESG-related mentions
🧩 Interpretation and opportunities: What could influence the decision
Example Output:
Comfort & Money: “turnkey solution” + “cost optimization”
Security: repeated mention of “verifiable references” and “required contractual guarantees”
⚠️ “Current supplier lacks responsiveness” → highlights importance of client support
🤖 Example Prompt
You are an AI assistant specialized in strategic RFP analysis.
Your goal is to read between the lines and extract deep motivations, potential barriers, and implicit concerns from the tender documents.
You should:
Analyze RC, technical specs, annexes, etc.
Identify non-verbalized expectations across these axes:
Rational buying criteria:
Price, brand, tech features, support, local availability
Purchase blockers:
Budget concerns, trust gaps, offer complexity, perceived risk
ESG criteria:
Environment: emissions, materials, waste
Social: working conditions, inclusion, local impact
Governance: transparency, compliance, anti-corruption
Your output should:
Include clear observations, based on weak signals
Highlight recurring or critical terms in bold
Be organized by analysis category, with bullet points
Flag ambiguous areas as “To clarify”
Do not paraphrase the RFP. Your job is to interpret it strategically.
✅ Benefits
Understand the buyer’s real motivations beyond formal specs
Adapt your response to match hidden expectations
Identify warning signs early and address them in your proposal
Strengthen your competitive positioning
Save time on in-depth analysis of dense documents
📌 Key Takeaway
This use case turns the AI into a strategic analysis co-pilot.
It helps you read between the lines of a tender to identify what truly matters in the client’s decision.
🎯 You’re no longer answering requirements — you’re responding to the buyer’s mindset.