LeanNav
LeanNav is a product discovery platform that helps teams test product ideas against real customer evidence before committing engineering resources. The platform gathers traceable customer quotes and problem signals from public reviews, forums, and communities, then ranks problems by evidence strength using proprietary scoring logic. Teams can practice interviews with evidence-based customer profiles and receive real-time coaching, with a one-week pilot delivering an evidence pack, problem scorecard, and interview guide.
- Enterprise Software
- Data & Analytics
- Software Only
Funding
Founders
Founder details are not available yet.
Product
Problem
AI has compressed the time and cost required to build software, yet deciding what is worth building remains slow, manual, and inconsistent. Product teams ship faster than they validate, and weak validation turns into wasted engineering and product investment. The information needed for sound product decisions exists but is fragmented across the organization and difficult to access.
Solution
LeanNav helps teams test risky product assumptions before they spend engineering time by providing a structured discovery and evidence scoring workflow. The platform gathers traceable customer quotes and problem signals from public reviews, forums, and communities, then builds an ideal customer profile and hypotheses from the user's product idea. Proprietary search and scoring logic ranks each problem by evidence level, with reports and research adding context. Teams can practice interviews with evidence-based customer profiles and receive real-time coaching to surface new assumptions and sharpen questions. Designed around a one-week cycle, LeanNav pushes validation decisions before sprint planning, pilot commitments, or roadmap decisions, ensuring that engineering resources are allocated only to validated bets.
Target Audience
Primary users are innovation teams, marketing professionals, and product managers who need to validate product ideas against real customer evidence before committing engineering time and resources.
Features
- Assumption-first validation workflow that prioritizes hypothesis testing before build commitments
- Evidence collection from public reviews, forums, and communities with every quote linked to its source
- Proprietary search and scoring logic that ranks each problem by evidence level, impact, and type
- Evidence-based customer profiles for interview practice with real-time coaching
- One-week cycle design for rapid decision-making aligned with sprint and roadmap timelines
- Decision-focused outputs that recommend build, pivot, or stop actions based on gathered evidence
- GDPR-governed data handling throughout the research process