ERP and cloud migration services for enterprise digital transformation
DataMTX is a 28-year-old IT services firm executing large-scale ERP migrations and cloud platform work. The tech stack reveals a heavy SAP/Infor/NetSuite focus, but the active projects and pain points show the company is actively moving clients OFF legacy systems—SAP CPQ to Infor CPQ conversions, Syteline to CloudSuite Industrial transitions—while layering AI integration into modernized platforms. Hiring is accelerating across engineering and specialist roles, with geographic distribution across US, India, and Sri Lanka indicating offshore delivery models.
Notable leadership hires: Database Director
DataMTX provides IT professional services and staffing solutions focused on enterprise system migrations, cloud infrastructure, and digital transformation. The company serves mid-market and enterprise clients in automotive, aerospace, ERP, and financial services sectors. Service lines span cloud migrations (AWS, Azure), ERP implementation and integration (SAP, Oracle, NetSuite, Infor), embedded systems and automotive infotainment, storage and infrastructure (IBM, HPE, EMC, NetApp), security and SIEM tooling, and QA/test automation. Engagement models include fixed-fee, time-and-materials, onsite/offshore, and managed services. Current project backlog centers on legacy system retirement, data cleanup, and embedding AI into existing enterprise platforms.
DataMTX has deep expertise across SAP (S/4HANA, CPQ, iDOC), Infor (CloudSuite Industrial, SyteLine, Birst), NetSuite, Oracle, Workday, and IFS. Current projects include migrating clients from SAP CPQ to Infor CPQ and transitioning legacy Syteline to CloudSuite Industrial.
Yes. Active projects include AI-driven development acceleration and embedding AI use cases into client platforms. Google Gemini and AI integration into legacy systems are key pain points the company is addressing.
DATAMTX LLC'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 →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.