Turn every outcome into intelligence. AI extracts 12+ insights from each debrief, updates competitive profiles, and feeds learnings back into the system—automatically improving every future proposal.
AI extracts actionable intelligence from win/loss feedback
Solicitation N0001425R0034 | Award Date: March 15, 2024
Winner's AI/ML Explainability Approach Superior
Government valued BAH's detailed LIME/SHAP integration. Our approach was too high-level. Action: Add explainability toolkit detail to future AI proposals.
Key Personnel Depth Insufficient
Winner proposed 3 PhDs in AI/ML vs our 1. Government feedback: "wanted deeper expertise." Action: Build AI/ML talent bench for future Navy pursuits.
Navy-Specific Experience Weighted Heavily
Winner had 5 Navy AI projects vs our 2. Evaluator noted "similar customer experience valued." Action: Prioritize Navy AI pursuits to build relevant past performance.
Price Sensitivity Higher Than Expected
5% price difference was significant factor. Government mentioned "budget constraints." Action: Sharpen price-to-win models for DoD contracts in current fiscal environment.
FedRAMP High Certification Was Differentiator
Winner's existing FedRAMP High reduced risk perception vs our "in progress" status. Action: Accelerate FedRAMP High certification timeline (target: Q3 2024).
Technical Volume Too Generic
Feedback: "approach could apply to any customer." Winner tailored heavily to Navy's unique data environment. Action: Increase customer-specific customization in technical approaches.
+ 6 more insights on teaming strategy, win themes, and competitive positioning
Solicitation FA864524R0018 | Award Date: February 22, 2024
"Zero-Downtime Migration" Resonated
Government cited our phased migration approach as key differentiator. Evaluator: "convinced us mission continuity was guaranteed." Action: Replicate this win theme structure for future migration RFPs.
DoD Cloud Experience Highly Relevant
Our 4 DoD cloud projects scored "excellent" relevance. Government feedback: "exactly the experience we needed." Action: Feature DoD cloud portfolio prominently in future Air Force pursuits.
Small Business Partner Added Value
25% small business subcontract to CloudTech Solutions exceeded requirement (15%) and brought niche cybersecurity expertise. Action: Continue aggressive small business teaming on Air Force pursuits.
AI feeds insights back into every phase of the process
AI extracts insights from debrief calls, emails, and formal feedback
Categorize by type, identify patterns across multiple pursuits
Update knowledge base: competitor profiles, win themes, pricing intel
Automatically improve future proposals with learned best practices
AI tracks competitor performance and updates profiles continuously
AI updates competitor profiles after every debrief, tracking strengths, pricing strategies, and win patterns
Four AI systems turning outcomes into intelligence
AI attends debrief calls, extracts insights from feedback, and categorizes learnings by type and relevance.
AI identifies trends across multiple pursuits: what wins, what loses, and why—by customer, contract type, and competitor.
Continuously updated competitor intelligence: capabilities, pricing strategies, win patterns, and relationship maps.
Learnings automatically update AI models across all 7 phases, improving future Pwin, win themes, and proposals.
How Phase 7 drives continuous improvement
Before: Learnings captured in Word docs, rarely applied to future pursuits. 6-12 month lag to incorporate feedback.
After: Insights applied to next proposal within hours. 3.2x faster learning velocity.
Before: 30-40% of debriefs captured due to manual effort, inconsistent format, lost tribal knowledge.
After: 94% of debriefs captured and analyzed by AI. 2.4x more intelligence.
Before: Repeating the same mistakes, stuck near industry win rates (~4%).
After: Continuous improvement loop stabilizing around a 22% win rate on supported bids. 5.5x improvement over traditional performance.
How Post-Award Learning multiplies your business development effectiveness
Hours vs Months
Insights applied to next proposal within hours vs 6-12 month learning lag with manual processes
94% Capture Rate
94% of debriefs captured and analyzed vs 30-40% manual capture rate - 2.4x more intelligence
22% Win Rate
Learning loop drives 22% win rate vs 4% industry average - 5.5x improvement from continuous improvement
