✓ Digital procedure checklists with photo attachments
✓ PM scheduling with automated triggers
✓ Parts and inventory tracking
What It Helps You Do
Mobile-first technician UX Built-in team messaging Highest-rated CMMS experience Strongly funded and scaling
What Sets Them Apart
Highest-rated mobile CMMS experience — designed for technicians who spend their day on the floor, not at a desk.
How MaintainX Uses AI
AI Claims Unverified Generative AI
HTMwire's independent read on the technology — not the vendor's marketing claim.
Markets AI features for work order categorization and analytics, but specifics on ML techniques used are limited.
AI work order assistance. Uses LLM-based features to help categorize work orders and draft task content from natural-language input, speeding up data entry for busy technicians.
Founded 2018 in San Francisco; led by co-founder and CEO Chris Turlica.
Reviews
G2 4.8/5
Investors / Funding
$254M total raised; Bessemer Venture Partners, Bain Capital Ventures, D.E. Shaw Ventures (Series D, July 2025, $2.5B valuation).
Frequently Asked Questions
Is MaintainX built for healthcare?
MaintainX is a mobile-first, general-industry work order and procedure platform, not healthcare-exclusive, but its digital checklists, messaging, and PM scheduling work well for HTM teams that prioritize technician usability over deep healthcare compliance features.
Is MaintainX well funded?
Yes. MaintainX raised a $150M Series D in July 2025 at a $2.5 billion valuation, bringing total funding to $254M. Investors include Bessemer Venture Partners, Bain Capital Ventures, and D.E. Shaw Ventures.
How is MaintainX rated?
MaintainX holds a G2 rating of about 4.8 out of 5, among the highest of any CMMS, reflecting its mobile-first design built for technicians on the floor.
Does MaintainX use AI?
MaintainX markets AI features for work order categorization, analytics, and natural-language task creation, but specifics on the underlying models are limited. Treat its AI as LLM-assisted productivity features rather than documented predictive ML.