PINNs, time accuracy & productivity.
How HawkLens uses physics-informed AI to improve total time, effective time, productive time — and what we’re shipping next.
What are PINNs? Physics-informed AI for real work time
Physics-Informed Neural Networks (PINNs) mix data with the laws of how systems evolve — so HawkLens can reason about time, not only count clicks.
The role of PINNs in better time management
PINNs help HawkLens turn raw activity into trustworthy time: total, accurate, effective, and productive — with fewer manual corrections.
Total time, effective time & productive time — explained
Not every logged minute is equal. Here’s how HawkLens separates total time, time accuracy, effective time, and productive time — and why it matters.
How physics PINNs improve time accuracy in HawkLens
We’re applying physics-informed models so total time, effective time, and productive time stay consistent — even when the workday is messy.
What’s next: PINNs features we’re shipping in HawkLens
A clear look at the PINNs-powered features coming to HawkLens — from smarter time accuracy to productive-time scoring and manager-ready reports.
Win back productivity & profits affected by distractions
Managers' time is expensive. Automated, non-intrusive tracking shows where time & efforts are spent — without losing yours.
Beyond time tracking
HawkLens is your organization’s Human Resource A/B testing tool. Find productive & distraction patterns after new HR policies, perks & rules.