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MeshInsights
AI agents that turn machine data
into trusted decisions.
MeshInsights develops and deploys AI agents that turn connected-product data into trusted operational decisions and action at scale, built on Mesh’s 20+ years of connected-product engineering experience.
Every decision MeshInsights automates starts as expert judgment. Somewhere on your team, someone already knows what a good call looks like for this workflow, they just can’t be everywhere at once.
MeshInsights takes that judgment, turns it into a standard an agent can be evaluated against, and lets the agent act where it’s earned the right to, escalating back to your experts when it hasn’t.
Expertise doesn’t get replaced. It gets encoded, scaled, and put to work.
Why Now
AI raised the stakes from digital enablement to competitive advantage, and what connected-product strategies have long pointed toward, turning machine data into decisions at scale, is now technically and commercially credible.
The Benchmark
An AI agent is a capable decision-maker off the shelf, but capability isn’t trust. MeshInsights starts by defining what a good decision looks like: a benchmark built from domain knowledge, real examples, telemetry evidence, and field outcomes. It’s a strategic asset your team owns, and how the agent is proven right.
The Practice Around It
A benchmark alone is inert. Mesh brings the practice around it, grounded in 20+ years of connected-product engineering experience: identifying the decision worth automating, assembling the right evidence from messy connected-product data, and keeping the benchmark current as your operations change.
Earned Autonomy
Trust is built in stages, not assumed. Agents prove themselves against the benchmark, run under supervision, then operate within proven boundaries, with low-confidence cases escalating to your experts as the standard for autonomy is met.
Agent Families
Five places to start.
MeshInsights is built for a recurring, high-value decision your team already makes, or knows it should be making. These five are the ones we see most often.
Early Warning
Detects degradation, failure risk, and abnormal behavior before problems become downtime events.
Service Resolution
Turns an alert into a recommended action: remote fix or dispatch, parts needed, escalation path.
Performance Management
Identifies waste, inefficiency, and capacity gaps across the installed base.
Aftermarket Growth
Finds commercial moments inside machine behavior and surfaces them as revenue actions.
Customer Health
Tracks relationship health through machine behavior: inactive assets, unresolved issues, churn risk.
Every MeshInsights agent is grounded in expert reasoning and proven against a standard you own.
Early Warning
A multi-site commercial HVAC operator
Manually set power-alert thresholds were quietly wrong for half the year, burying real problems in noise that analysts had to review one by one. An Early Warning Agent now recalibrates every unit’s threshold monthly against actual operating data, and flags any unit without enough history for a reliable call. A two-week prototype validated the approach. Trusted alerting now runs directly inside the existing platform, with no new tools required.
Service Resolution
A global manufacturer of industrial steam system components
Thousands of IoT-monitored components generated alerts, but each one needed an expert to confirm the failure and initiate service. The monitoring outpaced the people. A Service Resolution Agent, deployed in four weeks, now applies that expert reasoning automatically: determining failure mode, assessing confidence, and creating dispatch-ready tickets. Over 95% of service events now resolve end-to-end with no expert involvement.
Is MeshInsights right for you?
Mesh offers four solutions across the connected-product lifecycle: IoT Engineering Services builds the product, MeshCloud enables the data substrate, MeshInsights activates that data into decisions and action, and MeshManage operates all of it for the long term. Not sure where you fall on that spectrum? Talk to an expert and we’ll help you figure it out.
MeshInsights FAQs
How is this different from a dashboard or a predictive model?
Dashboards show you what’s happening and leave you to decide what to do about it. Predictive models flag anomalies that still need an expert to interpret them. MeshInsights closes that last gap: it defines the decision, builds the standard it’s judged against, and takes the action, escalating to your team only when confidence is low.
How do you validate that the agent is actually accurate?
Every agent is evaluated against a benchmark built from your own labeled examples before anything goes live. That benchmark defines what a correct decision looks like for your equipment, workflows, and failure modes, so you see accuracy against your data, not a generic claim. Confidence scores are surfaced on every decision, so your team always knows when the agent is certain and when a case should come to a person.
Our data isn't clean or well-labeled. Does that disqualify us?
Not in most cases. If your experts can make good decisions with your current data, those decisions can be automated. We start by working with your team to identify what data actually matters for the decision, assemble it in the right context, and build the benchmark from real, expert-reviewed examples. Data readiness is something we work through with you, not a prerequisite.
What do we own at the end of this?
You own the agent, the benchmark, and the labeled data behind it. It runs in your environment. Mesh owns its methods and platform IP, not the production host.
Ready to turn your connected-product data into decisions?
Tell us about the decision your team is trying to make reliably. We’ll show you what a benchmark and an agent look like for it.