
Superhuman
Superfilter AI
Shortwave
MailLM turns Gmail into a CRM-style inbox. Prioritize key contacts, capture tasks, draft replies, and automate follow-ups. Save 5+ hours a week.

FriendlyData
Infer SQL queries from plain-text questions and table headers.

Which is more popular?
Based on our record, mlsql seems to be more popular. It has been mentioned 2 times since March 2021.
Website, pricing, platforms and company facts side by side.
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| Website | maillm.com | github.com |
| Platforms | — | |
| Company | Startup from Australia · 10 - 19 employees | — |
| Listed in |
In their own words, as submitted to SaaSHub.


MailLM is an agentic AI email platform featuring CRM-style inbox, lead enrichment, task capture, and automated follow-ups. Helping teams nurture relationships, work smarter, and save time. MailLM is currently under development and will be available to customers within few months. Core features of...
No description of mlsql yet.
What each product offers, as listed by its team.


Possible disadvantages
No features have been listed yet.
An editorial look at what each product does well and who it suits.


Overall verdict
Why this product is good
Recommended for
Overall verdict
Why this product is good
Recommended for
How often each product is chosen within a category, 0–100% relative to the other.


As answered by people managing MailLM and mlsql.
MailLM's answer
It's specifically designed for all sorts of businesses.
MailLM's answer
MailLM is unique due it's CRM style inboxing, Smart Follow-Ups, automated drafts, AI driven triaging and many more.
Share your experience with using MailLM and mlsql. For example, how are they different and which one is better?
Recommendations tracked on public social media and blogs since March 2021.


Tracking MailLM since May 2025.
I am working on a project that requires me to take user input (as English) and return SQL queries. We will eventually be working with multiple datasets, which is why the valuenet over at https://github.com/paulfitz/mlsql ended up being... Source: over 4 years ago
I found this great resource here: https://github.com/paulfitz/mlsql. Source: almost 5 years ago
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