KDG Expands AI Assisted Agentic Development Model for Enterprise Software
KDG has expanded its AI assisted and agentic development services to accelerate enterprise software delivery, announced in a press release. The company described its model as a structured alternative to both traditional software development lifecycles and unstructured AI coding experiments.
The approach combines agent to agent workflows with engineering discipline to produce enterprise-grade prototypes in weeks and production systems in months. KDG integrates architecture, testing, infrastructure, and operational controls directly into the delivery process. Pricing begins at 25,000 dollars for prototypes and 50,000 dollars for production applications.
A key feature of the model is the use of automated testing agents that create unit, integration, and end-to-end tests from the start. These agents allow engineers to validate features quickly and maintain alignment across teams. The system supports environments such as Microsoft Azure, Google Cloud, and Zoho Catalyst.
Additional components include architecture-first delivery, behavioral change management systems, infrastructure as code, and knowledge management practices. The company stated that these elements ensure scalability, governance, and consistent engineering standards across projects.
We hope you enjoyed this article
Consider subscribing to one of our newsletters like Enterprise AI Brief, AI Programming Weekly or Daily AI Brief.
Also, consider following us on social media:
More from Enterprise
Oct 16 Nextech3D.ai Adds Agentic AI to Map D Event Platform Oct 16 McGraw Hill Adds AI Study Tools to Connect Oct 16 RapidCanvas Raises $29 Million to Expand Enterprise AI Platform Oct 16 Goodweek Raises $12 Million for AI Management Platform Oct 16 ALTOUR Unveils AI Platform for Corporate Travel DecisionsEnterprise AI Brief
Weekly report on AI business applications, enterprise software releases, automation tools, and industry implementations.
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
Kong outlines AI governance roadmap for Konnect
Kong AI Gateway 2.2 Adds MCP Access and Cost Controls
Arcadis Expands Autodesk Collaboration for AI Project Delivery
AutonomyAI Launches Discover Mode for Product Delivery
The Conference Board Proposes Five Stage Framework for AI Agents
Daily AI Brief: the AI news that matters, in your inbox.