Energy operations run where the cloud does not. Governance should too.

The energy and industrial numbers in Palantir's public materials are among the largest in the category, and they are curiously under-discussed: most commentary focuses on the software's AI framing rather than on what the customers report doing with it. Sources for everything below: Palantir's impact pages for Jacobs, Sonnedix, and Airbus, its supply chain offering page, all retrieved 2026-10-08.

The pattern: telemetry becomes setpoint changes

• Jacobs: 20% plantwide power savings at a water treatment plant, with electricity usage per million gallons treated reduced from roughly 2,000 KWh to about 1,500 KWh.
• Sonnedix: 100% remote monitoring of solar trackers across its monitored sites, with an expectation to reduce revenue losses from tracker failures by at least 20%.
• Airbus: A350 production up 33%, with an estimated $1.7B a year in savings identified (Palantir's supply chain offering page); Airbus and Palantir co-built the Skywise aviation data platform in 2017.
• An industrial customer: $200M saved over 24 months, including $40M of logistics optimization in the first 120 days.

Remote monitoring at 100% coverage is still, on its own, watching. The savings arrive when watching turns into setpoint changes: rerouting a pump load, rescheduling a tracker row, re-sequencing a production line, expediting a component. Those are writes into plant systems and ERPs, executed under time pressure, often by software. That is an action layer, and in this industry it lives at the edge, on-prem or in private infrastructure, close to the machines and far from comfortable cloud assumptions.

Why this industry demands self-hosted by design

Three structural reasons, none of them marketing:

• The data is operationally sensitive. Plant telemetry, production schedules, and maintenance states reveal capacity and constraint. Operators treat this the way banks treat positions: it does not leave the perimeter by default.
• The network is not reliable. Energy assets run on constrained, sometimes air-gapped links. An action layer that stops when the internet blips is, in a plant, a liability. The governance layer has to run where the plant runs.
• The writes touch physical outcomes. A setpoint change on the wrong unit is not a bad dashboard tile. Proportionate control, proposals staged, policies evaluated per action, critical changes stopped for qualified humans, is how the industry already thinks about safety, and software governance should meet that bar rather than lower it.

Three questions for any platform pitched at your plant

• Does it deploy fully inside our boundary, including its governance and audit components, with no cloud dependency for core operation?
• Can it write back to the systems that run the plant, through governed proposals, rather than only reading data out?
• Can our engineers replay any automated decision, end to end, without contacting the vendor?

If the answers are no, yes, and no, you are being sold a dashboard with an edge deployment plan. The provable trust properties and the approval loop are the working alternative.

Where Syntheka stands

Syntheka is a governed action layer built to run inside your perimeter: staged proposals and runtime policy enforcement on every write path, multi-node approval with segregation of duties, an append-only, hash-linked evidence chain in your own database, and governed write-back to SAP where industrial planning and maintenance terminate. The energy and industrial results above are the pattern we built for, with the deployment model the industry actually requires. The cost page and the platform overview are the honest starting points; your plant is the real test.