Foundpoint reads from the systems your operation already runs on — sensor historian, ERP, maintenance management, fleet — and surfaces the structure between them. One operational view. Built for on-prem, sovereign, and intermittent environments.
If any of these sound like your week, we already understand the rest.
Your morning meeting spends an hour reconciling spreadsheets before anyone can ask a real question. Maintenance and dispatch disagree about which trucks are down and why.
A vibration alert appears on a primary asset. Three to five days pass before a work order is dispatched. The data was there. The connection between the systems was not.
Asking "which trucks in Pit 3 are within 200 hours of scheduled maintenance and showing vibration anomalies" requires four queries, four logins, and an engineer's afternoon.
Your general manager has dashboards. Your general manager does not trust the dashboards. They are reconstructed manually, in PowerPoint, the night before the review.
It is not a replacement and it is not a rip-and-replace. It reads from the systems you already run on, maps their data into a unified operational graph, and exposes that graph two ways — through a working application your operations team uses, and through an API your existing BI and control-room tools can consume.
Equipment-health, alerting, and action workflows in a working UI your team uses directly. The same operational graph exposed via REST and GraphQL for the BI and control-room tools you already trust. We do not ask you to learn a new place to look.
A haul truck is not a row in a table. It is an object with relationships — to its sensors, its operator, its maintenance history, its dispatch route, its fuel-consumption record. The ontology engine maps your raw tables into operational objects with typed relationships, so a single query can traverse what was previously four queries and three manual joins.
Custom adapters for the systems industrial operations actually run: sensor historians, ERP, maintenance management, fleet management, MES, certification systems. We do not depend on fragile community connectors. Each adapter is built for the system it talks to, and built to survive an intermittent connection.
Edge-first architecture. Async sync. Designed for satellite, VSAT, and remote-site connectivity with 200–2000ms latency and regular outages. The platform stays usable when the link to head office does not.
No customer data leaves the customer environment unless the customer chooses it. Air-gapped deployment supported. Compatible with regional sovereignty and data-residency requirements.
Runs on a single virtual machine for a small operation. Scales to a three-node cluster for a large multi-site group. Does not require a dedicated cloud-ops team to keep alive.
PostgreSQL underneath. Open standards. Your data remains your data, in a schema your team can read, query, and export. We are infrastructure, not lock-in.
Foundpoint is in active deployment dialogue with one tier-one operator. We have capacity for a small number of additional design partners during the first deployment cycle. We engage on a deployment briefing first — no procurement process, no demo theatre.
A briefing is a 60-minute conversation with your operations and IT leads. We learn the shape of your operation. You learn whether Foundpoint is built for the conditions you actually run in. If both answers are yes, we go further.