PRNewswire
Englewood (Colorado) [US], May 6: Nomiso, a leader in co-engineering and AI-driven solutions, today announced the launch of its Smart Agent Framework, coinciding with its four-year anniversary. The new platform empowers enterprises to create domain-specific AI agents, delivering faster, more precise solutions for complex business challenges.
Built on Nomiso's core philosophy of first-principles thinking with deep domain Knowledge, the Smart Agent Framework extends the capabilities of out-of-the-box AI by integrating enterprise-specific knowledge bases and fine-tuning on proprietary data. Early deployments in Telecom Network and IT Operations and Fintech product development have shown dramatic improvements in software release velocity, defect detection accuracy, and breakthrough productivity in operations.
"Innovation happens when you design for the problem, not around it," said Anil Jain, CEO of Nomiso. "The Smart Agent Framework helps organizations move from idea to impact faster with solutions built for their unique challenges, not off-the-shelf templates."
"Generic AI often falls short inside enterprises," added Chandra Narayanasamy, CTO of Nomiso. "Our framework bridges that gap by delivering adaptive, domain-centric intelligence that drives real business outcomes."
With this launch, Nomiso continues its mission to help enterprises unlock the true potential of AI, turning complex problems into real-world growth opportunities.
For more information, visit nomiso.io.
About Nomiso
Nomiso is a software co-engineering company that partners with its clients in solving complex business problems with technology. Their problem-solving approach and product-thinking mindset helps businesses create differentiated solutions at speed and scale to drive enhanced value outcomes.
Logo: https://mma.prnewswire.com/media/2679392/Nomiso_Logo.jpg
(ADVERTORIAL DISCLAIMER: The above press release has been provided by PRNewswire.will not be responsible in any way for the content of the same)
Disclaimer: This post has been auto-published from an agency feed without any modifications to the text and has not been reviewed by an editor