Nomic Refocuses Platform on AI for the Built World
Nomic AI has announced a new platform focused on accelerating AI adoption in built world industries such as energy, engineering, architecture, and construction, according to an announcement on the company's website.
The new Nomic Platform is designed to handle the complex, multimodal data typical of built world projects, including architectural drawings, structural designs, and engineering specifications. These documents often combine 2D and 3D data formats that standard vision and language models struggle to interpret accurately.
Nomic’s approach includes domain-specific embedding, parsing, and vision-language models built to process high-resolution design files and large-scale documentation. The company states that its AI systems are already helping designers and engineers save significant time on quality control, document retrieval, and rework.
CEO Andriy Mulyar said the platform aims to become the standard AI system for professionals working across the built environment. Nomic plans to continue developing custom models and infrastructure that enable production-grade AI agents to operate effectively over engineering and construction data.
We hope you enjoyed this article
Consider subscribing to one of our newsletters like Enterprise AI Brief or Daily AI Brief.
Also, consider following us on social media:
More from Enterprise
Oct 2 Mews Launches AI Guest Messaging and Hotel Automations Oct 2 Slang AI Adds BentoBox Cofounder Krystle Mobayeni to Board Oct 2 Barclays Expands Claude Use Across Software Development Oct 1 SmartAC Launches Gen2 HVAC Sensor and Intelligence Model Oct 1 Workday Launches UAE Operations With Dubai OfficeIndustrial AI Weekly
The latest advancements in smart manufacturing, predictive maintenance, AI-driven quality control, supply chain & more.
Whitepaper
Tensordyne Napier: What If One Rack Could Do the Work of Nine?
Tensordyne
This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.
Read moreYou may also like
Overmind Open Sources Platform for Specialized AI Models
Infrastructure AI Introduces Agentic Asset Valuation for Buildings
Nextworld Named an Accelerator in 2026 LCAP Matrix
Nuix Adds Generative AI Tools and AI Chat to Discover
Noma Security Extends Agent Controls to Employee Endpoints
Daily AI Brief: the AI news that matters, in your inbox.