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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Slow Training Data Labeling
Teams struggle to create, clean, and maintain high-quality labeled datasets for training and evaluating models.
In their words
Anything that reduces the number of frames we have to pay to annotate is quite valuable.
The dataset is forever, and it's the part that rots.
i already neglect my linkedin, i'll neglect this too unless it's mostly hands-off.
I am looking for a high-quality, 100% synthetic CPG dataset for training purpose.
working on a project about hand data collecting, can we talk to see if can buy your product
does anyone have insight into this specific problem — cheaply telling "faceless but real" content apart from actual decorative/text junk
it turned an hour of skimming into two minutes of typing
I need a baseline and a gold standard before we go live but it looks like I'm manufacturing the ground truth out of thin air.
we burn through it once, call it done, and cripple our own progress.
our testing has basically been me and one other engineer eyeballing outputs in staging before each release, plus whatever users report after
It’s not uncommon for one person to correct 5k images a day while the offshore team does about 10k/wk at around 1k hours/wk.
I need a baseline and a gold standard before we go live but it feels like I'm basically manufacturing the ground truth out of thin air.
Managing the training data and doing DINO->YOLO distillation has me writing my own data management suite that I plan on OSing soon.
We hit that exact wall building our AI features and ended up with synthetic data that didn't generalize well.
ML and CV teams
Where they talk
- r/computervision
- r/StableDiffusion
- r/datasets
- r/AI_Agents
- r/LLMDevs
- r/LocalLLaMA
- r/artificial
- r/mlops
Tools they use today
- Claude
- Braintrust
- Excel
- Roboflow
- YOLO
- CLIP
- huggingface
- MLflow
Why those fall short
- high friction, users default tag everything
- files won't download, archives corrupt, access approval process is heavy
- data scarcity and quality remain the bottleneck, not architecture
- clunky, manual, relies on eyeballs
- Synthetic personas cannot generate the failures that actually hurt
Map of ideas
Drawing the map…