Inspect
features .01mm or in different spectra
Defense aviation maintenance faces a critical inflection point. With a projected shortage of 48,000
maintenance workers by 2027, aging legacy fleets requiring intensive inspection regimes, and zero
tolerance for missed defects in mission-critical systems, traditional inspection methodologies can no
longer meet operational demands.
ARACHNID autonomous inspection platform is a fundamental shift from
slow, reactive maintenance to an AI-driven predictive system that detects sub-millimeter defects
while reducing inspection time by 85% and costs by 60-75%.
features .01mm or in different spectra
data at fleet scale
Strategize your work to make the most of your team.
Defense aviation maintenance faces a critical inflection point. With a projected shortage of 48,000
maintenance workers by 2027, aging legacy fleets requiring intensive inspection regimes, and zero
tolerance for missed defects in mission-critical systems, traditional inspection methodologies can no
longer meet operational demands.
ARACHNID autonomous inspection platform is a fundamental shift from
slow, reactive maintenance to an AI-driven predictive system that detects sub-millimeter defects
while reducing inspection time by 85% and costs by 60-75%.
features .01mm or in different spectra
fleet scale data sets
Strategize your work to make the most of your team.
Defense aviation maintenance faces a critical inflection point. With a projected shortage of 48,000
maintenance workers by 2027, aging legacy fleets requiring intensive inspection regimes, and zero
tolerance for missed defects in mission-critical systems, traditional inspection methodologies can no
longer meet operational demands.
ARACHNID autonomous inspection platform is a fundamental shift from
slow, reactive maintenance to an AI-driven predictive system that detects sub-millimeter defects
while reducing inspection time by 85% and costs by 60-75%.
features .01mm or in different spectra
fleet scale data sets
Strategize your work to make the most of your team.