Tecnoprism launches Automation COE platform for enterprise automation at scale

Tecnoprism on June 30 announced Automation COE, a platform that combines AI-driven process discovery with runtime assurance to help enterprises cut automation costs, reduce failures and speed up delivery. The launch targets the growing gap between automation adoption and reliable outcomes across large workflows.

Why it matters: - Enterprises are scaling automation across thousands of workflows, but many programs still run into discovery gaps, rework and runtime failures. - Tecnoprism is positioning Automation COE as a way to lower total automation costs and improve reliability as automation becomes business-critical. - The platform is aimed at reducing manual effort, preventing SLA breaches and improving return on automation investments.

What happened: - Tecnoprism announced the launch of Automation COE on June 30, 2026. - The platform is designed for enterprise customers. - Automation COE connects AI-driven process discovery with proactive runtime assurance. - Tecnoprism said the product is now available to enterprise customers.

The details: - The launch addresses three pressure points in enterprise automation: process discovery, development and runtime reliability. - Tecnoprism says nearly 70% of organizations have already implemented automation in at least one business function. - Gartner estimates that up to 30% of automation initiatives fail to deliver expected results because of poor process understanding and governance gaps. - Industry research shows that more than 90% of enterprises report downtime costs above $300,000 per hour, with many above $1 million per hour. - Tecnoprism said 98% of organizations report automation-related issues contributing to SLA breaches. - At the discovery layer, ARIA, or Automation Requirements Intelligence Agent, analyzes recorded workflows to capture actions, decision points and variations. - ARIA is meant to replace manual interpretation and generate structured outputs for automation. - Tecnoprism said automated discovery approaches can compress discovery timelines by as much as 90% while improving accuracy. - At the operational layer, AURA, or Automated Uptime and Runtime Assurance, validates system readiness before execution and monitors runtime behavior for risks before failure occurs. - AURA is designed to address cascading failures in interconnected automation environments. - Tecnoprism cites financial services operations as an example where a dependent application delay can stall multiple automated processes and trigger transaction backlogs and manual intervention. - Tecnoprism estimates integrated approaches like Automation COE can reduce overall automation lifecycle costs by 30% to 45%. - The company says the platform can also accelerate time to value and improve return on automation investments.

Between the lines: - The launch reflects a shift from “more automation” to “better automation systems,” with emphasis on governance, reliability and lifecycle management. - Tecnoprism is framing automation as an operational discipline, not just a deployment problem. - The combination of discovery and runtime control suggests the company is targeting the hidden costs that often show up after automation goes live. - Tapan Patel, Tecnoprism co-founder, said automation is now limited less by execution and more by how well processes are understood and how reliably systems run in dynamic environments.

What's next: - Tecnoprism will push Automation COE to enterprise buyers looking to scale automation without adding hidden cost and risk. - The company is betting that proactive runtime assurance will become a standard requirement as automation expands into more business-critical operations. - Tecnoprism will likely use its broader AI and automation services footprint to support adoption across North America, MENA, Southeast Asia and APAC.

The bottom line: - Tecnoprism is trying to own the layer between automation design and automation reliability, where many enterprise programs lose time, money and performance.