In short: Athena Technology Solutions, a Fremont-based MES integrator with roughly 120 employees, has launched FabOrchestrator, an agentic AI platform for manufacturing that automates reporting, support tickets, system modeling, and code generation for semiconductor and electronics factories. Built in partnership with Bangalore-based LLM at Scale.AI, it layers LLM capabilities on top of the Siemens Opcenter and Critical Manufacturing MES platforms that Athena implements.
Athena Technology Solutions, based in Fremont and employing around 120 people, has introduced FabOrchestrator, which it labels as the manufacturing sector’s first “Agentic AI Foundry,” aimed at automating reporting, support tickets, system modeling, and code generation within semiconductor and electronics factories.
Developed with LLM at Scale.AI, a Bangalore-based enterprise AI platform, the product incorporates large language model capabilities into the manufacturing execution systems Athena installs for its clients. It anticipates that the agentic AI trend transforming software development and customer service can also apply to the highly specialized, data-intensive environment of a production fab.
What FabOrchestrator does
The platform features four components. FabInsight allows factory engineers to query production data using plain English, obtaining reports and analyses without needing to write SQL or use multiple dashboards. An AI Support Engineer automatically resolves routine MES support tickets, referring complex issues to human engineers. A Modeling Agent responds to MES configuration questions and guides teams through system upgrades. A Back-end Agent creates code snippets to speed up MES implementation tasks.
None of these features are completely new. Natural-language querying of enterprise data, automatic ticket triage, and AI-assisted code generation are services offered by numerous companies across various industry sectors. Athena is attempting to package these specifically for manufacturing execution, where the data structures, workflows, and domain knowledge are specialized enough that general-purpose AI tools often yield unreliable results.
“This is a major advancement for the MES ecosystem,” remarked Senthil Ranganathan, Athena’s founder and CEO. Established in 2011, Ranganathan has two decades of experience in manufacturing systems within the disk drive, semiconductor, and solar industries.
The MES context
Manufacturing execution systems are the software backbone of any modern factory. They monitor every wafer, component, and assembly throughout the production process, documenting what occurred, when, by which machine, and under what circumstances. In semiconductor fabs, where a single chip undergoes hundreds of process steps over several weeks, MES data is both critical and extensive.
Athena is addressing the problem that extracting value from this data usually demands specialized knowledge. Writing reports requires understanding the MES data model. Configuring the system for new products involves navigating complex modeling rules. Troubleshooting issues necessitates knowing which of thousands of parameters might be relevant. These tasks consume engineering hours that could otherwise be devoted to improving yield or throughput.
Athena serves as an implementation partner for Siemens Opcenter and Critical Manufacturing, two major MES platforms used in semiconductor and electronics manufacturing. Its business revolves around deploying, customizing, and supporting these systems. FabOrchestrator signifies an effort to layer AI on top of this existing expertise, transforming the domain knowledge their consultants hold into something deliverable as software rather than billable hours.
The partnership
The AI platform that powers FabOrchestrator is from LLM at Scale.AI, a Bangalore-based company founded in 2023 specializing in multi-agent orchestration for enterprise applications. The company boasts clients like JTC, CBRE, JLL, Cushman and Wakefield, Johnson Controls, and the State of California, mainly in facilities management and real estate. Its research collaborations include MIT, UC Davis, and NTU Singapore.
The partnership is commercially sensible for both parties. LLM at Scale.AI gains access to manufacturing domain expertise and a customer base it would have difficulty reaching independently. Athena receives an AI platform without having to develop one from scratch. The key question is whether the combination works reliably on a factory floor, where incorrect data or a misdirected process step can be costly.
Market timing
Athena is entering a market that larger firms are also targeting. Microsoft’s industry blog noted that 65% of manufacturers plan to implement AI-powered MES by 2026. Infor, Siemens, and other prominent industrial software vendors are