Sentinel AI Physics-informed · Closed-loop

Stop reacting.
Start optimising.

Optvance deploys autonomous AI above your existing control systems and turns reactive energy operations into self-optimising assets. No rip-and-replace, no new infrastructure, no production disruption.

ISA-95 control hierarchy
Sentinel AI optimisation layer L3.5
RTO / APC L3
DCS / PLC / SCADA L2
Field instruments & sensors L1
90Days to measurable value
21Sentinel AI modules
3Industries served
$0New infrastructure
EPRIMember of the EPRI ConsortiumElectric Power Research Institute
The problem

$1.5T in O&G revenue, and 70% of assets run without AI

Legacy DCS, SCADA and APC react after problems occur. Manual judgement at every critical decision point compounds value loss across the operation.

Production inefficiency

Reactive control leaves value on the table at every well, every shift and every decision point.

2–5%production lost per asset each year

OPEX leakage

Structural inefficiency in energy and chemical spend compounds and is hard to isolate by hand.

10–30%leakage in energy & chemical spend

Brownfield constraint

Full replacement is not economic. Intelligent augmentation of what is already installed is the practical path.

70%of global O&G assets are brownfield

AI adoption gap

Other industrial sectors are already transforming. Energy operators have a narrow window to move first.

<10%AI adoption in O&G today
Sentinel AI platform

The intelligence layer above your existing systems

Sentinel AI sits above SCADA, DCS and APC. Physics-informed models run in advisory (open-loop) or autonomous (closed-loop) mode, with full auditability.

Sense more

Unified data layer

Historians, SCADA, lab data and edge sensors combined into one operational picture.

Understand better

Physics + ML

Pattern recognition bounded by physical constraints finds relationships traditional APC cannot see.

Predict earlier

1–2 hours ahead

Forecasts instability, degradation and process excursions before value is lost.

Optimise continuously

Open or closed loop

Recommendations or autonomous setpoint control, retrained as the asset changes.

Deployment pathway

From first asset to enterprise scale in under 12 months

Phase 1

Asset identification

Pick target assets, baseline KPIs, validate sensor coverage and agree measurable success criteria.

A clear target with quantified upside
Phase 2

Proof of Value

Build prediction models on 6–12 months of history, run in simulation and test what-if scenarios.

>80% prediction accuracy target
Phase 3

Online deployment

Run in advisory mode on live assets, measure uplift and train operators on real evidence.

Evidence-backed business case
Phase 4

Enterprise scale

Automate across the process with dashboards, governance and continuous model retraining.

Autonomous optimisation at scale
Try it

How ready is your operation for AI?

Operational Intelligence Readiness Portal

A five-minute assessment. An AI agent researches your organisation first, then maps your operational pain points to the right Sentinel AI modules. Separate flows for operating companies, technology partners and system integrators. Every report is reviewed by the Optvance team before it reaches you.

  • Company research agent runs before the questionnaire
  • Low / Medium / High readiness score with a percentage
  • Recommendations across all three Optvance verticals
  • iOS and Android apps with full feature parity
Patent pendingWeb + mobileAdmin-reviewed reports
Start with one asset

A 90-day Proof of Value.
Zero capex.

We baseline one asset, prove the uplift on your own data, and only then talk about scale.

Talk to the team →