Quartic offers an AI‑powered Manufacturing Operations Management (MOM) platform that unifies OT and IT data into a real‑time industrial data fabric. By applying sample‑efficient AI and optimization algorithms, it delivers predictive quality, reliability analytics, and automated decision logic that reduce variability, accelerate cycle times, and lower quality‑related costs for process manufacturers.
Funding
$20M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Manufacturers in process industries such as life sciences, chemicals, CPG, and food & beverage often operate with fragmented data sources, manual decision processes, and limited real‑time visibility, leading to variability, lower yields, longer cycle times, and higher quality‑related costs.
Solution
Quartic provides an intelligent Manufacturing Operations Management (MOM) platform that unifies operational technology (OT) and information technology (IT) data into a real‑time industrial data fabric. The platform applies sample‑efficient AI and optimization algorithms to generate context‑rich insights, predictive quality and reliability analytics, and automated decision logic that can be executed at speed without disrupting existing workflows. By delivering connected, responsive, and agile decision support, Quartic enables manufacturers to reduce variability, accelerate cycle times, improve yields, and lower laboratory and maintenance costs across regulated and high‑volume production environments.
Target Audience
Primary customers are process manufacturers in life sciences, specialty chemicals, consumer packaged goods, and food & beverage seeking to modernize their MOM systems and gain AI‑driven operational intelligence.
Features
- Event‑driven industrial data fabric that links OT, IT, and enterprise systems for real‑time data ingestion and synchronization
- Sample‑efficient AI models and multivariate data analysis (MVDA) for predictive quality, yield optimization, and root‑cause diagnostics
- Automated decision systems that execute logic‑based actions (e.g., batch adjustments, maintenance triggers) with minimal manual input
- Predictive operations and reliability modules that forecast equipment failures and recommend proactive interventions
- Scalable deployment from a single production line to enterprise‑wide networks without disrupting GxP or existing workflows
- Integrated dashboards and APIs that provide actionable insights to process engineers, quality teams, and maintenance personnel