Every phase is bounded, produces standalone technical deliverables, and ends with a clear go/no-go decision. NIMBUS never asks customers to fund a large rollout before problem severity and failure signals are proven.
The sequence reduces uncertainty progressively: first about problem severity, then about signal quality, then about operational ROI.
Start with a free 20-minute discovery conversation. A paid two-week Discovery is used only when scope, evidence or access are not yet mature enough for Assessment.
Build an evidence-based view of criticality, condition signals and the monitoring gaps worth addressing.
Validate a bounded monitoring workflow on a small asset set, with success criteria agreed before deployment.
Scale only after the pilot demonstrates useful evidence in the customer’s own operating context.
The Asset Health Assessment is structured to leave engineering teams with valuable technical assets even if no pilot follows.
The initial 20-minute discovery conversation has no charge. Baseline fees pre-qualify initial scope, while final proposals account for asset count, site complexity and data access.
A focused founder-led conversation to test whether there is a real asset-health problem worth scoping.
A short 2-week engagement when scope, asset access, or data maturity are not yet ready for Assessment.
A four-week assessment of asset criticality, condition evidence, and pilot opportunity.
A bounded six-to-eight-week validation on a small, agreed asset set.
We evaluate machine health without requiring direct access to plant networks or sensitive production recipes.
Initial assessments rely on static CSV exports, Historian snapshots, or offline sensor captures. We never demand permanent inbound firewall ports or IT network integration during early stages.
All dataset ingestions strip batch numbers, chemical formulas, and proprietary product names on-site before analysis. Only physical machine variables (vibration, current, temperature, pressure) are processed.
Live telemetry during pilots is encrypted in transit (TLS 1.3) and at rest (AES-256) inside containerized microservices. Your plant data is never aggregated or used to train external models.
All asset-health risk registers, baseline envelopes, and failure mode calibrations delivered are your property. If an engagement stops, temporary staging files are purged upon request.
NIMBUS is founder-led by Sergio Matolla, combining quantitative analytics, high-throughput data engineering credentials, and industrial reliability principles.
Business & Data Engineering professional specializing in large-scale automated data pipelines, multivariate time-series anomaly detection, and cryptographic systems.