Manoj Yadav

Niyam AI - Build Discipline - Get Direction - Attain Consistency.

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Niyam AI is a Slack-based time tracking tool that helps teams build and follow schedules without any friction. People don’t log time accurately. They either forget, batch hours at end of day, or have to switch into a separate tool (timers, spreadsheets, project software). Niyam AI lives inside Slack. You message it like you normally would — describe what you’re working on — and it automatically extracts the task and time spent. No forms, no timers, no context switching.

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Manoj Yadav
Maker
📌
Hey PH 👋 The honest origin story: we were so bad at time tracking that we tried literally everything. Toggl, Harvest, built-in timers in project tools. All of them had the same problem — the moment you had to open a separate app and start a timer, you just… didn't. Or you did it at 6pm for the whole day from memory, which is basically fiction. The thing we realized is the friction isn't laziness. It's context switching. You're deep in something, you finish, and the last thing you want to do is go log it somewhere. So with Niyam, you just message the bot in Slack when you're done with something. That's it. "Just wrapped the client call" or "done with code review, took about 45 mins" — the bot pulls out the task and the time and logs it. You're already on Slack. It's two seconds. When we ran it internally, we found 3–4 hours of untracked idle time every week per person — the gaps between meetings that disappear into thin air. That's not small. That's half a workday. Curious if anyone else has solved the "I'll log it later" trap — and what actually worked. Always down to talk 🙏
Tarun Patel

Hey 👋 Tarun here — I built the product.

Not used to writing these so I'll keep it simple.

When Manoj first explained the idea, it genuinely seemed like the most obvious thing nobody had done yet. Time tracking that lives where your team already talks. No new tool to open. No habit to form. Just Slack.

That clarity made it easier to build. When you know exactly what you're solving for, the technical decisions almost make themselves.

The part I'm most proud of is how little the user has to think. You describe what you did in plain language — the way you'd tell a colleague — and the bot handles the rest. Getting that to feel natural took a lot of iteration, but I think we got there.

Excited to see how real teams use it and what breaks first. That's honestly where the interesting work begins.

If you have technical questions or feedback, happy to answer anything here 🙏

Daniel Nwankwo

Congrats on your launch! It's actually an amazing tool.

Manoj Yadav
@daniel_nwankwo thank you for the appreciation, let me know if you have any feedback while you use it