Zensory.ai™ — Autonomous wellsite intelligence

Emissions intelligence that sees the whole site.

Zensory.ai™ fuses optical gas imaging, acoustic monitoring, and AI vision to find fugitive emissions, hear equipment failure coming, and watch every remote site — continuously, autonomously.

Records everything Alerts only on what matters LDAR-aligned
0+
Years of experience
0+
Remote sites monitored
0+
Videos analyzed per site, per day

Operating since 2012 — Sapulpa, Oklahoma

01 / The problem

The cost of driving blind

Five structural challenges face every oil & gas professional running remote assets on periodic inspections.

01

Regulatory demands

Quarterly LDAR inspections are expensive and provide only periodic compliance snapshots — leaving operators exposed to undetected leaks between cycles.

02

High operational costs

Route-based site visits cost mid-sized to large operators $1M–$5M+ annually.

03

Lost profit

Periodic monitoring cannot define the duration of a leak — or the volume of methane lost — resulting in poor repair and maintenance ROI decisions.

04

Safety risks

Unproductive travel exposes field personnel to traffic accidents, adverse weather, and hazardous site conditions.

05

Environmental impact

Unnecessary vehicle miles add carbon emissions and increase the operational environmental footprint.

02 / The platform

Detection is easy. Discernment is everything.

Competing platforms treat every signal as suspicious, overwhelming operators with alerts that don't require action. That distracts from the real work of emissions mitigation.

Zensory.ai™ doesn't just detect — it discerns. It learns the difference between normal process emissions and fugitive emissions: the needle in stacks of needles, the one abnormal event hidden inside layers of normal activity.

Don't alert about the stack. Alert about that one needle.

Live — Site 114 Fugitive anomaly — alerted
Zensory.ai™ — acoustic channel Baseline learned

Process emission

Logged — no alert

Fugitive emission

Operator alerted

04 / Operate by exception

Record everything. Alert only on what matters.

Operate-by-exception failed when it was SCADA graphs alone. Zensory.ai™ gives remote teams the same sight, sound, and smell they trust onsite — so the exception model finally earns trust.

Step 01

Learn the site

Machine learning establishes each site's normal baseline in roughly two days — across load conditions, weather, and routine operational activity.

Step 02

Detect & validate

Multi-sensor fusion — video, audio, OGI — scores every event against the baseline. Process emissions are logged. Fugitive anomalies are validated.

Step 03

Alert with evidence

Near real-time alerts to the Well Checked dashboard, email, text, and SCADA via API — every alert supported by visual evidence operators interpret instantly.

"If all our sites are continuously monitored, when a fugitive gas event occurs — which it will — we are proactively alerted and our team can acknowledge, dispatch, then mitigate within 24 hours. Rapid response can minimize or eliminate EPA fines."
Director of Operations — Operator customer

Success story

How a leading gas producer cut drive time and saved $1M annually

Annual savings
$1M+
Site visits
Daily → monthly
Monitoring leverage
24h saved per 8h

Read the story

Get started

Speak with a member of our team today.

See Zensory.ai™ on your own sites. Pilot programs run alongside your existing LDAR cycles — no leap of faith required.