All ideas
SaaSDifficulty: Medium
AI Agent Workflow Analytics: See how users actually interact with your agent before scaling
Build AI features that people actually use by analyzing real user workflows before you waste engineering cycles.
The signal
“And wondering why they keep collapsing Here's what's actually happening in 2026: The Al-First Graveyard Hundreds of startups raced to ship Al features. ChatGPT integration. Autonomous agents. Al copilots. Zero understanding of their users' actual workflow. Zero validation of the ”r/aiagents — read the original
Why it scores 75
Demand
8
Enterprise teams urgently need proven AI workflows but waste resources on speculative AI features that fail to integrate with actual business processes.
Competition
6
Many AI toolkits exist but few offer validated workflow patterns or concrete ROI case studies, leaving room for practical solutions.
Feasibility
9
MVP can be built in days using existing LLM APIs and open-source workflow frameworks, focusing on documentation and templates.
Timing
7
Current enterprise AI disillusionment creates strong demand for practical, workflow-first solutions over speculative AI features.
MVP build path
The full MVP path, competitor teardown and keyword data are part of the paid database.
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