# Inside NYC DDC’s Enterprise AI Transformation

Customer: New York City Department of Design & ConstructionIndustry: Government & Public SectorUse Case: Rollout & Activation within a Public Sector AgencyProduct: Claude Enterprise								
				
					Overview				
				
									SVAM helped NYC DDC become one of the first NYC agencies to roll out Claude Enterprise and Claude Code. DDC manages the city’s $34B capital construction portfolio. The deployment went from first briefing to about 85 licensed users with enterprise security and governance in place from day one.								
				
					Challenges				
				
									The New York City Department of Design and Construction (DDC) is the City’s primary capital construction agency. It manages a $34 billion portfolio of civic infrastructure, including libraries, firehouses, police precincts, sewers and water mains. As the City puts new emphasis on government efficiency and fiscal responsibility, DDC is looking for ways to deliver projects faster, make better use of staff time and modernize how the agency operates.DDC ran a thorough evaluation of Claude’s capabilities, security controls and total cost of ownership. It chose Claude Enterprise and Claude Code as the platform to support its efficiency goals. The initial focus areas include:Streamlining manual, document-intensive workflows to improve accuracy and turnaround timeModernizing legacy applications by generating documentation and speeding up updates to older systemsAccelerating software development through AI-assisted coding, testing and quality assuranceCentralizing institutional knowledge so staff can easily find and ask questions about agency policies and procedures								
				
					Results				
				
									Delivered to dateDeployed Claude Enterprise and Claude Code to approximately 85 users in DDC. It is one of the first enterprise-wide Claude deployments at a New York City agency.Took the engagement from first briefing to production rollout while meeting City security, procurement and executive approval requirements.Set up enterprise controls from day one: SSO, audit logging, data governance and usage limits. Target outcomes (first 12 months)Adoption: 75%+ of licensed users active each month, with licenses extended to more DDC divisionsDevelopment speed: 25–30% less time spent on routine coding, testing and code reviewLegacy modernization: documentation for priority legacy applications produced in days instead of weeksWorkflow efficiency: 30–40% less manual effort in selected document-intensive processesKnowledge access: staff find agency policy and procedure answers in minutes instead of hoursStaff capacity: thousands of staff hours a year freed up for higher-value work Next phase: Measure baselines and results against these targets. Expand to more use cases and divisions, and give other City agencies a reusable model for adopting AI securely.