Introduction
Praemo is headquartered in Kitchener, Canada founded in 2017 and is covered in Brel’s AI in Manufacturing sector. Leadership referenced in company materials includes Paul Boris.
Public company materials describe the firm as building AI software for manufacturing workflows. Brel’s working summary of the product scope: Provides industrial data analysis software utilizing machine learning to compute operational risk models.
This profile uses only company-linked sources captured during the 2026-07-10 import review. Funding, valuation, headcount, and ranking claims from third-party listicles are omitted unless a company-specific URL in the source list supports them.
What the company does
Praemo positions its product around the following use case: Normalizes disparate automation data to extract prescriptive maintenance schedules. Secondary focus noted in research intake: Predictive Analytics.
Buyers should treat vendor marketing claims as unverified until confirmed in a live evaluation against their own data, compliance, and integration requirements.
Who it serves
Stated buyers and users include: Heavy manufacturing automotive and process industry plants
Procurement teams should confirm whether the deployment model (SaaS, on-prem, hybrid) and data-residency options match their sector obligations before pilot expansion.
Company background
Praemo operates from Kitchener, Canada. Company materials cite 2017 as the founding year. Paul Boris is listed as founder or CEO in the intake sources used for this profile.
Brel does not infer prior employers, investor syndicates, or competitive rankings without a company-specific citation.
Product and AI capabilities
Within Manufacturing AI, Praemo concentrates on: Normalizes disparate automation data to extract prescriptive maintenance schedules.
Exact model architecture, training data rights, and evaluation harnesses are rarely fully disclosed on marketing pages — request technical documentation during vendor diligence.
Key developments
Recent development noted in intake (verify on the linked company page before citing externally): Developed unified asset anomaly maps for high-throughput casting lines.
Why it matters
Praemo matters for Brel readers tracking Manufacturing AI because it represents an active vendor in this category with a verifiable public website and company-linked documentation. Its stated focus — Normalizes disparate automation data to extract prescriptive maintenance schedules. — is a concrete buying motion teams can compare against peers in the same sector hub.
Use the AI in Manufacturing hub to compare adjacent profiles; do not treat directory presence as an endorsement.
Sector context
Praemo is filed under Brel’s AI in Manufacturing coverage, with secondary theme Predictive Analytics. Country taxonomy reflects headquarters (Canada), not customer geography.
Sources and references
Primary references used for this profile:
- Praemo — official source — https://praemo.com/platform
- Praemo — supporting company page — https://praemo.com/team/
Last reviewed 2026-07-10. Request a correction via the form linked on this page if a fact is outdated.