London-based Applied Computing raised a $20M Series A led by KBR, with Databricks Ventures participating. Its Orbital foundation model combines time-series, physics and language modeling to predict plant state, find anomalies and simulate fixes.
Company
Applied Computing
Department
Refining, LNG & process operations
Record type
pending_review
Disclosed stage
As described in supplied reference; review pending
Source date
2026-07
Source-date precision
month
Source provenance
D · Secondary / unverified
Review disposition
Access or verification limitation; inspect profile and source history
Reported result
$20M Series A; 'double-digit millions' ARR within ~18 months; facilities use <8% of sensor data
What this does not establish
Imported claim and interpretation from the supplied reference. Source text, date, scope and outcome attribution require independent verification.
Strategic investors (an engineering firm and a data platform) give distribution, and a hybrid physics-time-series-language model is attracting funding.
London-based Applied Computing raised a $20M Series A led by KBR, with Databricks Ventures participating. Its Orbital foundation model combines time-series, physics and language modeling to predict plant state, find anomalies and simulate fixes.
A source grade describes provenance, not independent verification. This is a research profile, not a measure of net return. Report a correction.