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.
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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.
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LLM API Cost and Routing
Teams struggle to manage multiple LLM providers, control costs, and route requests reliably without rewriting code or overspending.
In their words
The benefit here is that it's probably it's the cheapest way to get a good model with virtually no rate limits.
90% of the time it's extremely slow. This has been for the past 2 days since I've been subscribed
Answer question to content of a PDF (possibly 100+ pages of legal text, thus 32GB VRAM over 24GB)
Models randomly return 500 errors from cloudflare with no rhyme or reason, and absolutely no status updates from cloudflare.
connect the ai to our knowledge base (locally hosted docmost) - it should be able to work without any issues with up to 100 users connected from almost every continent.
I wanted an assistant that could take some of the load of managing 1000 things off me.
my agents routinely sabotage my projects... I am looking at making a drastically different work flow for actually sensitive projects
the search is kind of broken with DDG and I really don't want to use API keys from Brave or Google
We run into massive accuracy drops the second prompt engineering hits mixed Hinglish or regional context
A normal customer message can consume around 8,000 tokens, and when the bot places an order usage can spike to 30,000-35,000 tokens
What are the cheapest agent models that still have a high success rate with JSON outputs and function calling?
Right now, the process seems to involve trying dozens of prompts, copying results into a spreadsheet, checking competitors
We want the most powerful models, we're willing to pay for them, but we see over and over how much of a frontier the frontier actually is.
as someone who lives in claude code all day, the context-window gauge is the part i'd open this for, watching it silently fill until things degrade
LLM developers and teams
Where they talk
- r/LLMDevs
- r/LocalLLM
- r/LocalLLaMA
- r/ClaudeAI
- r/ClaudeCode
- r/codex
- r/AI_Agents
- r/mcp
Tools they use today
- Claude
- ChatGPT
- OpenRouter
- Claude Code
- Qwen
- LiteLLM
- Gemini
- DeepSeek
Why those fall short
- thinking fills context window and VRAM quickly
- 24GB VRAM too small for 100+ page legal PDFs
- 5hr limit prevents burning 800m tokens in a few hours
- slow 90% of time, context capped at 200K instead of 1M
- frontier models refuse spec features and waste tokens on sensitive workflows
Map of ideas
Drawing the map…