AI-powered mobile platform for frontline operations in asset-intensive industries
Innovapptive builds a mobile-first operations platform targeting the Office of the COO in heavy industries—oil & gas, chemicals, mining, utilities. The tech stack reveals deep ERP integration (SAP MM, Oracle EBS, Infor, JD Edwards) layered with AI/ML foundations (LangChain, CrewAI, vector databases: Pinecone, Weaviate, Qdrant, Chroma). Engineering-heavy hiring (15 of 24 open roles) focused on senior and lead levels suggests they're scaling integration complexity and AI capabilities rather than pure feature velocity. Active projects around SAP MM integration, BADI enhancements, and Maximo workflow indicate they're positioning themselves as the execution layer for enterprise asset management systems.
Innovapptive provides an AI-powered, mobile-first platform that unifies frontline work execution, maintenance, operations, safety, and supply chain teams for asset-intensive industries. Founded in 2012 and headquartered in Houston, the company serves 50+ global enterprises across oil & gas, chemicals, mining, and utilities sectors. The platform connects field workers with configurable mobile applications for inspections, work execution, and digital instructions, while back-office teams gain real-time visibility and intelligent planning through integrated analytics. Innovapptive is a SAP certified mobile application partner and actively extends SAP MM, Oracle EBS, and IBM Maximo ecosystems through low-code/no-code configuration and AI-driven predictive capabilities.
SAP (MM, PM, HANA), Oracle EBS, IBM Maximo, plus AI/ML: LangChain, CrewAI, Pinecone, Weaviate, Qdrant, Chroma. Also integrates SCADA, MES, OSI PI, Aveva, Honeywell, Yokogawa, AspenTech for industrial operations data.
SAP MM integration, Maximo workflow integration, BADI enhancements, cloud asset management delivery, and real-time data pipelines. Core focus: connected worker platform deployment and value realization across maintenance and operations teams.
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Innovapptive Inc's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
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