Evidenso Product & Market Intelligence Graph
Decide What Is Worth Building Before AI Writes the Code
Evidenso builds a Product & Market Intelligence Graph that helps builders and AI agents validate product opportunities before development starts.
Instead of generating ideas in isolation, AI systems can query real signals about users, markets, competitors, and product context.
In the age of AI coding agents, building is easy. Deciding what to build is the real challenge.
Example Output
Immediate proof for builders and agents
Builder prompt
Should we build collaborative dashboards for product teams?
Evidenso response
Opportunity assessment
High potential for product teams in data-driven startups
Opportunity score
0.74
Segments affected
Evidence signals
Confidence
High
Sources
Product communities, competitor release notes, user research interviews
This is how builders and AI agents validate product opportunities before building them.
The Problem
AI Can Build Anything. Most Features Still Don't Get Used.
AI coding agents can generate features, prototypes, and entire applications extremely quickly.
But the hardest question remains unchanged: what should we build in the first place?
Most product teams still struggle with feature adoption. A large percentage of shipped features are rarely used or fail to solve meaningful user problems.
The intelligence required to evaluate opportunities is typically scattered across research documents, analytics dashboards, competitive analysis, conversations, and intuition.
AI accelerates execution, but without the right intelligence it often produces outputs that are fast but poorly validated.
The Solution
The Product & Market Intelligence Graph
Evidenso connects product context and market signals into a structured intelligence layer. Signals become linked intelligence that both humans and AI agents can query.
Nodes represent key entities: users, problems, features, competitors, experiments. Relationships capture how these entities influence one another.
The result is machine-readable product intelligence that supports validation and decision-making.
Product Intelligence
Internal product context, structured
Internal product context becomes structured intelligence for consistent decision support.
Market Intelligence
External signals, linked to decisions
External market signals are structured and linked to product opportunity analysis.
How AI Agents Use It
MCP, APIs, and agent integrations
The intelligence graph is accessible through MCP, APIs, and agent integrations. AI agents can retrieve product and market intelligence directly during product work.
How It Works
Evidence-backed answers through a simple mental model
AI Agent→MCP / API→Evidenso Intelligence Graph→Evidence-backed answers
The graph becomes a shared intelligence layer for both humans and AI systems.
Where the Intelligence Comes From
Product context and market signals, continuously linked
Product context
Market signals
These signals are linked into the Product & Market Intelligence Graph.
What Builders Actually Get
Decision artifacts, not just stored context
These outputs help teams evaluate opportunities before committing engineering time.
Why This Matters
Execution is easy. Decisions are critical.
When AI makes building software extremely fast, the constraint shifts. Execution becomes easy. Decisions become critical.
Evidenso helps teams evaluate product opportunities using real signals about users, markets, competitors, and product context. Builders and AI agents can make decisions that are evidence-grounded rather than intuition-driven.
Long-Term Vision
The graph becomes organizational product intelligence
As teams work, the system accumulates insights, experiments, decisions, and outcomes. This compounding intelligence improves how organizations understand users and evaluate opportunities.
Instead of starting from scratch each cycle, teams build on validated knowledge that grows over time.
Build with Context-Aware AI
Connect your product context and enable AI agents that understand users, markets, and product strategy
Connect your product context, explore the intelligence graph, and validate product opportunities before building.