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METR, 2025

AI was supposed to make your team faster. Instead, it made it 19% slower.

Same hours · Same team · Better outputs.

The Model

The Model
Chronotype
Personal peak window
Ultradian rhythm
~90-minute cycle
Attention residue
~20-minute recovery
Recovery architecture
Structured return to baseline
01 — Read

Calendar, Slack, Linear — already open on your screen. Timing and structure only. Message content is never stored, analysed or logged.

02 — Surface

In the calendar, before you save the meeting. In Slack, before someone gets interrupted.

03 — Adapt

Sprint week one looks different from week six. Vatta knows the difference.

The science behind Vatta

The evidence

Mental fatigue, cognitive strain, and decision friction are now the leading indicators of burnout — surpassing workload volume for the first time.

Deloitte Workforce Intelligence, 2025
$322B

Lost annually to cognitively depleted knowledge workers.

Gallup
23 min

Average time to regain deep focus after one interruption.

Gloria Mark, UC Irvine
19%

Slower using AI tools, despite predicting they'd be faster — echoing a separate finding that 77% feel AI added to their cognitive load rather than reducing it.

METR, 2025 · Culture Amp
Privacy

Three rules we don't break.

Nothing new to open or monitor. Vatta reads what your team already has.

No individual scores.
Never content.
Always team-level.
Team

The Berkeley students behind Vatta.

Anna Bhogra
Cognitive & data science. Thesis at the intersection of cognition and computation. Leading 75 engineers at Berkeley. Product & Analytics at Underdog Fantasy.
Aryan Achuthan
Data science. National Chess Master, #11 in the US at 18. SWE at Google and IBM. Product & Engineering at Business & Software at Berkeley (BSB).

Every tool your team uses shapes the conditions they work in. Most weren't designed to.

Vatta is.

vātāvaraṇa — Hindi for atmosphere.