These days, positioning itself as an “industrial AI platform” company, IFS is known to many for its track record in ERP, asset management and field service maintenance technologies.
As the organization now works to validate its vision for industrial intelligence across its six key verticals, IFS used its showcase customer, partner and practitioner event in New York this week to detail what it says are significant new partnerships with Anthropic and Boston Dynamics.
On Topic With Anthropic
In pursuit of deeper infrastructure intelligence for the age of industrial AI, IFS has partnered with Anthropic via IFS Nexus Black, a cloud-based service that connects enterprises and suppliers for real-time supply chain visibility. The union between the firms sees the launch of Resolve, a technology layer that puts industry-specific AI in the hands of frontline field workers in industrial hangars, plants and factories.
Kriti Sharma, CEO at IFS Nexus Black, insists this is no cosmetic corporate love-in; it’s a connection of technologies focused on responsible, safe AI that is that’s non-negotiable. This is the application of AI in services in industries where, some days, life is on the line, such as aerospace & defense, construction & engineering, manufacturing, energy, utilities & natural resources and telecoms.
“Anthropic combines frontier AI capabilities with the safety and reliability that industries require. IFS has unquestionable expertise in the complex realities of the industrial world; it has proven it can activate and apply AI in capital-intensive and asset-heavy environments. Together, we’re deploying AI where the stakes are highest,” said Garvan Doyle, applied AI lead at Anthropic.
Multi-Modal Mode
Functionality here includes the power to predict and prevent faults faster by interpreting multi-modal data such as video, audio, temperature & pressure and complex schematics. It will connect the right technician to the right part, in the right place, with optimized scheduling.
“Resolve reads complex plant schematics, plugs into existing sensors to predict failure before it happens and diagnoses faults based on what engineers actually need,” explained IFS’ Sharma and team. “Technicians use Resolve to diagnose faults based on the sound of a rattling pipe, video showing how a part’s moving strangely, or fluctuations in pressure.”
Boston Dynamics, Woof!
Known for its incredible four- and two-legged robot creatures (the “dog” is known as Spot), Boston Dynamics is also working with IFS. The new partnership is designed to help asset-intensive organizations manage and optimize their field operations.
Uniting Boston Dynamics’ autonomous inspection robots with the IFS.ai is said to create a fully agentic AI system that connects sensing, predictive decision-making and action in the field. With labor and skills shortages impacting industrial customers, leading to service gaps and prolonged outages, IFS suggests that there is an identifiable need for technology that can supplement field workers.
According to Dr. Merry Frayne, director of product at Boston Dynamics, the company’s Spot robots inspect industrial assets and sites, capturing critical operational data in real-time.
Hazardous Harm Helpers
Spot uses thermal cameras to detect overheating, it can listen to air or gas leaks, read analog gauges for pressure and flow, check indicator lights, identify hazards like spills, or detect voltage anomalies. This information feeds directly into IFS.ai, where agentic AI analyzes the data, makes intelligent decisions, and triggers appropriate actions – creating a loop that runs from sensing to execution. Autonomous inspections reduce human exposure to hazardous environments while increasing inspection frequency and thoroughness.
“Asset-intensive organizations face unrelenting pressure to improve operational performance. Together with Boston Dynamics, we’re delivering an autonomous system that connects the physical and digital worlds for the first time. IFS.ai and IFS Loops turn robot observations into enterprise action, from preventative maintenance scheduling to predictive failure analysis and automated anomaly detection,” said Christian Pedersen, chief product officer, IFS.
As data now flows from the field into enterprise systems, decisions can be made autonomously, but (despite all the industrial automation being showcased here) it seems clear that there will still be a human-in-the-loop element of any prudently crafted architecture deployment in this arena.
How we actually apply the grade of autonomous control that any given service, model, engine or agent can work with may well be the next biggest question in AI, industrial or otherwise.
