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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Fragile Manual Data Pipelines
Data teams struggle with brittle, manual, and costly ETL/ELT pipelines that break silently, lack validation, and are hard to maintain or scale.
In their words
My company wants to replace Fivetran with easier and cheaper alternative.
my current setup using DLT requires Python for any custom connector work. I'm not sure my team is there yet.
They had an ETL import that would fail every night because it couldn't resolve some keys because the import order was wrong.
Where I'd love a seasoned second opinion is the PowerSchool side specifically: getting the plugin and read-only scopes right without disturbing the live SIS
I do not think Lakeflow is production worthy
It’s just another day when we have another billion+ row TB+ table to move.
ninguém me informou que tinha uma limitação de req por mês
on mondays, someone manually copies numbers into a google sheet because that’s the version leadership actually reads
real-time ingestion is the most overprescribed thing in the modern data stack and i say that as someone who has built it and regretted it
Every interface takes an eternity to load... I have to just start over.
Since there is no partition, and the files are tiny, it is impossible to use Athena to query the data.
every time an API updated or a folder structure changed, our custom python connectors broke.
The old software we are using is at the end of it's life-cycle. It was never the best piece of software and we built a lot of workarounds within and around it.
I just want to be able to check a box somewhere and have a table in Postgres automatically mirrored to Iceberg, with guarantee that no data is lost.
Data engineers
Where they talk
- r/dataengineering
- r/databricks
- r/MicrosoftFabric
- r/snowflake
- r/automation
- r/PowerBI
- r/Database
- r/analytics
Tools they use today
- Databricks
- Microsoft Fabric
- dbt
- Snowflake
- Fivetran
- Kafka
- PostgreSQL
- Python
Why those fall short
- AI cheats, hard-codes data, duplicates logic, cannot be tested or audited
- webhook delivers raw disorganized JSON, no structure for analysis
- One error anywhere breaks the entire sequential run; no separate dev environment
- no tests, no spec, nobody remembers why weird behavior exists
- Schema evolution is a train wreck; custom code needed to avoid breakage
Map of ideas
Drawing the map…