SaaS ideas your next customers are already looking for
100 SaaS startup ideas for the people who said they'd pay, from agency owners to dentists. Micro SaaS ideas, AI SaaS ideas and B2B SaaS ideas: find yours, build it, sign them up.
Popular:
| # | Idea |
|---|
No idea matches this filter.
Pain points in business: what people struggle with
Search the problems to solve, as people described them on Reddit and other platforms, in their own words.
Popular:
| # | Pain point |
|---|
No pain point matches this filter.
AI Agent Governance Gap
Organizations deploying autonomous AI agents lack the identity, permission, audit, and lifecycle controls needed to govern them safely in production.
In their words
I have no list, no visibility, nothing to point at when an auditor asks where our customer data is actually going.
I care most about stopping a bad action in the moment and about evidence I can hand to audit.
how to protect company data once agents start interacting with internal systems and third party apps without someone watching every step
I'd also want to know exactly what the agent can access and what it can do before permitting it
A days-long agent with write access and a connector to everything is only as safe as the access you handed it
None of the "non human identity" platforms make any sense
Wie löst ihr Auth, Kontext und Auditierbarkeit?
tracking the actual decision-making and data access paths of an AI agent is where it gets iffy
non-human identities with standing access nobody reviews
nobody owned it, nobody monitored it, nobody would have noticed if it started doing something unexpected
cada team está cómo gallinas sin cabeza haciendo agentes de todo tipo, y ya proliferan cómo hongos
how do you decide what's actually worth an agent vs a plain deterministic workflow, and how do you keep track of everything that's running?
I haven't yet seen a great security governance model for LLM integrations.
The human-in-the-loop approach kills the autonomy promise, but uncapped spend is a non-starter for any serious business.
AI platform and security teams
Where they talk
- r/AI_Agents
- r/AI_Governance
- r/AskNetsec
- r/cybersecurity
- r/LangChain
- r/mlops
- r/LLMDevs
- r/aiagents
Tools they use today
- Claude
- MCP
- Claude Code
- Codex
- n8n
- Cursor
- LangChain
- Microsoft Entra
Why those fall short
- no delegated scoping, no change control, no audit of AI actions
- MCP/CLI management tools offer little value and are impossible to enforce
- SCCM misses scripts and containers; config tools only see configs you feed them
- no unified auth, context and audit governance for agent actions
- no built-in approval or guardrail for AI agent actions
Map of ideas
Drawing the map…