Design, simulation, failure analysis, test data, manufacturing and quality live in disconnected tools. ME.ai links every artifact — from requirement to quality record — into one verified, auditable thread.
// FOR OEMs · HARDWARE STARTUPS · ENGINEERING FIRMS — NO SPAM, EVER
CAD in one silo, FEA in another, test data on a shared drive, DFMEA in a spreadsheet, 8D reports in email. When something fails, reconstructing why takes weeks — if it's possible at all.
Design intent dies between departments. The simulation team analyzes rev C while manufacturing tools up rev D.
A safety factor in a report with no visible formula, assumptions, or validity range. Nobody can audit it — so everybody re-derives it.
DAQ output sits in folders, never systematically compared against the simulation that predicted it. The loop never closes.
Every module is independent — adopt one, or all seven. Each writes to the same traceability spine, so your engineering record assembles itself as you work.
End-to-end docs generated from the work itself — specs, calc reports, drawings packages. Every number in every document links back to its source formula and inputs.
Parametric design with intricate detail control — STEP/IGES in and out, versioned geometry, and design decisions recorded as first-class artifacts, not tribal knowledge.
FEA, CFD, vibration, acoustics and coupled physics — run as managed jobs, with every result tied to the exact geometry and load case it came from.
DFMEA, FTA and root-cause work seeded from your own design and simulation history — not a blank spreadsheet.
Sensor and DAQ integration with experimental setup plans and clean rig diagrams. Measured data streams in and lands next to the prediction it tests.
CAM and CIM-aware handoff: manufacturable intent, process notes and tolerances flow to production with full context attached.
8D, Lean Six Sigma and QAP workflows wired to live sensor checks — every quality record traces back through manufacturing, test, simulation and design to the original requirement.
Incumbent stacks are acquisitions bolted together — their data models can't agree. ME.ai is built on one spine from day zero: every artifact is a node, every dependency a typed link, the whole graph queryable and auditable.
Every calculated value carries its formula source, assumptions, and validity range — like σ_max = Mc/I · [Shigley §3-10]. Auditable by any engineer, any regulator, any time.
DAQ measurements are automatically correlated against the simulations that predicted them. Model error becomes a tracked metric — your predictions get better with every test.
Import CAD, calc sheets, test data or quality docs. ME.ai structures them into artifacts on the spine — no rip-and-replace, no big-bang migration.
Run calcs, simulations, DFMEAs and test campaigns inside modules. Every output is checked for units, validity range and cited method before it's committed.
Impact analysis, audit packages, compliance reports and end-to-end documentation — generated from the graph your work already built.
A small cohort of OEMs, startups and firms will define what the next decade of engineering software looks like. Take a seat at that table.