How Ankur Gupta is making AI model deployment more reliable

At LinkedIn, Ankur Gupta helped cut median AI model deployment time from two days to 2.5 hours while raising deployment success to approximately 96%.

AI Native Application Development Platform Market by Technology, Pricing Model, and Deployment, 2026-2032 | Agentic AI and LLMs Unlock Enterprise Productivity and Growth

Slash technical debt and SaaS costs with AI-native platforms, hyper-agile teams, and autonomous agents that streamline refactoring, testing, and deploymentDublin, Oct. 20, 2026 (GLOBE NEWSWIRE) -- "AI ...
databricks.com

How FactSet cut model training and deployment from days to hours with Databricks AI Runtime

FactSet’s Text-to-Formula (TTF) system converts natural-language requests from investment professionals into FactSet Query Language (FQL) formulas. After an initial RAG approach hit a quality ceiling ...

The License Comes After the Weights: Deployment-Restriction Convergence as the New Open-Weight Normal

The $20M Revenue Ceiling Enterprise deployers are discovering that open-weight models no longer guarantee operational autonomy. A quiet convergence is underway, centering on a $20 million revenue ...
HackerNoon

FLock.io Launches Qwen-powered, Open-Source Decision Model for Local Edge Deployment

B, FLock.io and Oxford University researchers have launched an open-source AI decision model that outperforms Jev and larger ...
techtarget

Blue/green deployment on the cloud makes updates easier

With system isolation, ease of replication and rapid deployment, virtual infrastructure is the ideal way to run preproduction testing, system integration and production staging. It has become the ...