
Chronoid
Rize
Timing
RescueTime
Fomi
Your Mac already knows how you work. Now you will too.

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 | tenexaitbd.com | github.com |
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What each product offers, as listed by its team.


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An editorial look at what each product does well and who it suits.


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


As answered by people managing tenexaitbd.com and mlsql.
tenexaitbd.com's answer
10ex is a productivity coach that runs entirely on your Mac. It tracks which apps you use and when, then analyzes your work patterns using an AI model that runs locally on your device. Your data never leaves your computer.
Most productivity tools either take screenshots of your screen or send your activity to the cloud for processing. 10ex does neither. It observes behavior only (which apps are active, how long you spend in them, when you switch between them) and runs all AI analysis on-device using a bundled language model. There is no account to create, no data uploaded, and no telemetry.
The analysis goes beyond simple screen time. 10ex measures deep work sessions (focused stretches of 45 minutes or more), tracks context switching frequency, detects contradictions in your habits (like apps you open often but barely use), and identifies momentum trends over weeks and months. It combines algorithmic pattern detection with AI-generated coaching to surface insights that a simple time tracker would miss.
tenexaitbd.com's answer
Privacy enforced by architecture, not just policy. The AI model runs locally. There are no analytics SDKs, no cloud processing, and no user accounts. Your work patterns stay on your Mac. This isn't a marketing claim you have to trust on faith. It's how the software is built.
Depth of insight, not just time totals. Screen time trackers tell you how long you used an app. 10x tells you whether that time was deep, focused work or shallow task-switching. It tracks your deep work streaks, compares today to yesterday, spots when your habits are drifting, and offers specific coaching like "Try protecting one 25-minute block tomorrow morning." It learns your patterns over 7, 30, and 90-day windows to surface trends you can't see in a daily summary.
It coaches, it doesn't judge. 10x celebrates your wins ("Your longest focus block was 24% above your baseline") and asks reflective questions ("What helped today?"). The system is built around encouragement and small, actionable suggestions.
tenexaitbd.com's answer
10x is built for knowledge workers on Mac who care about doing focused, meaningful work and want to understand their patterns without giving up their privacy.
The typical user works in long creative or analytical sessions: developers, writers, designers, researchers. They know that deep focus is their most valuable resource. They're familiar with ideas like deep work and intentional time management, and they want real data about their habits rather than guesswork.
They've probably looked at other productivity trackers and been put off by screenshot capture, cloud uploads, or shallow "you spent 3 hours in Chrome" reporting. They want something that respects their intelligence, respects their privacy, and gives them useful feedback on how they actually work.
Share your experience with using tenexaitbd.com 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 tenexaitbd.com since Mar 2026.
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: almost 5 years ago
I found this great resource here: https://github.com/paulfitz/mlsql. Source: almost 5 years ago
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