Uptake
Predictive maintenance software for truck and equipment fleets that flags problems before a breakdown, with Bosch now acquiring the company.
A shop-floor system that connects CNC machines to an AI assistant called Max, which tracks downtime, flags problems, and answers plain questions.
MachineMetrics is a manufacturing execution system built around machine data. It connects directly to CNC machines and other shop-floor equipment to track what is actually happening in real time. Production managers use it to track downtime, machine utilization, scrap, and tool life, and its scheduling feature updates automatically based on how machines are actually performing, not just the original plan. A built-in AI assistant called Max AI writes shift summaries, gives setup guidance, and flags problems before they turn into scrap; staff can also ask it questions in plain language and get answers grounded in real machine signals. The platform connects to ERP and CMMS systems through open APIs. One customer reportedly connected 86 machines within a single week.
This fits a discrete manufacturer running CNC machines or similar equipment across one or more shops, and operations and continuous improvement teams that want real machine data instead of manual paper logs. A practical pilot is connecting one cell or one department first; the vendor has shown fast onboarding for dozens of machines. Pricing is not published, so treat any number as a planning estimate until you get a formal quote. The AI features work best once real machine and work-order data is flowing in, and results improve after the first few weeks. One thing to check: confirm which machine types and controllers the tool supports before you buy, since older or unusual equipment may need extra integration work.
These estimates cover licensing, setup, integrations, staff time, security, administration, and support.
| Cost measure | Low | Base | High |
|---|---|---|---|
| First-year total | $103.3K | $161.7K | $258.8K |
| Three-year total | $226.3K | $339.9K | $522.5K |
| First-year cost per unit | $103.3K | $161.7K | $258.8K |
| Average annual cost per unit (over three years) | $75.5K | $113.3K | $174.2K |
| Component | Low | Base | High |
|---|---|---|---|
| Licensing and usage | $37.5K | $50K | $67.5K |
| Implementation | $16.8K | $28K | $47.6K |
| Integration | $17.6K | $32K | $57.6K |
| Staff time and change management | $10.5K | $15K | $21K |
| Security | $7.7K | $11K | $16.5K |
| Administration | $5.6K | $7.5K | $10.1K |
| Support | $2.6K | $3.5K | $4.7K |
Estimate assumptions: Based on 1 production deployment. This is a planning allowance, not verified product pricing. Confirm the vendor’s billing unit and current price or quote before budgeting.
Benefits have not been estimated: The current research does not estimate potential savings, return on investment, or how long it would take to recover the cost. Earlier benefit estimates are excluded.
Confirm current product identity, commercial packaging, data processing terms, sign-in and access rules, retention, integrations, support model, implementation effort, and rollback conditions.
Verify identity, package, availability, ownership, pricing, and security evidence before approving a pilot
Do not approve a pilot yet. Verify the current product identity, package, availability, owner, pricing, and security evidence; then define one workflow, a baseline, and rollback criteria.
Define what success looks like for a test of MachineMetrics and assign someone to lead it.
Once the requirements above are met, compare a small trial with how your team works today.
Track adoption, output quality, business results, and actual costs against the estimate.
Use the results to decide whether to stop, adjust, or expand the pilot.
Confirm encryption, how the vendor uses your data, customer data separation, how long data stays and how to delete it, activity records, sign-in and user setup, where data is handled, other companies that process data, past incidents, and what your team must manage.
Review before rollout: confirm how to export your data, revoke access, and return to your existing workflow. Assign an owner and test the rollback plan before expanding use.
Do not approve a pilot yet. Verify the current product identity, package, availability, owner, pricing, and security evidence; then define one workflow, a baseline, and rollback criteria.
Predictive maintenance software for truck and equipment fleets that flags problems before a breakdown, with Bosch now acquiring the company.
A no-code computer vision tool that lets quality teams build models to spot visual defects without writing code or hiring data scientists.
A predictive maintenance tool that forecasts equipment failures from sensor and maintenance data and adds a chat assistant for engineers.
Royal HaskoningDHV (Lanner)
Simulation software for modeling factories and supply chains before making real changes, now sold by Haskoning under its Twinn brand rather than by Lanner.
Where to check the product, price, security, and support.
Recorded score and category rank across research updates.
Answer a few questions about your company and compare this tool with others. The research score above stays the same.
Want help moving from research to action? Explore TriVista’s AI consulting services →