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Accelerating a Construction Tech's Product Roadmap by 9 Months

A major construction enterprise needed to develop a proprietary, AI-powered safety and efficiency monitoring system but faced a significant internal challenge: a shortage of specialized computer vision talent and a long, competitive hiring cycle. To accelerate their time-to-market, they partnered with Evren AI, embedding our elite AI engineers directly into their team to build and deploy a sophisticated computer vision platform in record time.

Industry:Construction Technology
Core Challenge:Internal Talent Shortage & Slow Product Development
Solution:AI Staff Augmentation, Embedded Engineering Team, Computer Vision
Accelerating a Construction Tech's Product Roadmap by 9 Months
Challenge illustration
Challenge illustration

The Strategic Imperative: Build Internal Capabilities, Faster

Overcoming the AI Talent Bottleneck

The client struggled to quickly hire qualified AI engineers, delaying product development. Immediate access to top talent was needed.

Ensuring Real-Time, On-Site Performance

The system required low-latency video analysis on construction sites with limited or no cloud connectivity, needing a reliable Edge AI solution.

Integrating with Existing Site Management Systems

The new AI system had to seamlessly integrate with the client's existing project management software for unified site management.

We had the vision, but we didn't have the specialized talent in-house to execute quickly. Bringing Evren AI's team on board was like hitting the accelerator. They integrated seamlessly with our engineers, brought world-class expertise to the table, and helped us launch a mission-critical product in a fraction of the time it would have taken us otherwise.

Chief Technology Officer

Major Construction Enterprise

Our Blueprint for Accelerated, Collaborative Development

Embedded an Elite Team of AI Engineers

Deployed a team of computer vision specialists to work alongside the client's R&D, handling model training and deployment on NVIDIA hardware.

Implemented a High-Throughput Edge AI Pipeline

Built a real-time video analytics pipeline using DeepStream SDK, enabling simultaneous processing of multiple video streams with high accuracy.

Drove a Collaborative, Knowledge-Transfer Process

Engineers worked closely with the client's team, transferring knowledge and best practices to ensure the system could be managed and expanded in-house.

Focused on Building a Scalable, Integrated Solution

Ensured the system could scale to hundreds of sites, while integrating smoothly with existing management systems for a unified solution.

Enterprise AI System

The Transformational Outcome: Accelerated Time-to-Market and a New Competitive Advantage

Product Launch Accelerated by an Estimated 9 Months

Eliminating the hiring cycle and leveraging our team's expertise allowed the client to launch their AI safety system ahead of schedule, gaining a first-mover advantage.

From Kick-off to Multi-Site Deployment in Under 6 Months

Our integrated team model enabled rapid development and deployment, demonstrating the efficiency of staff augmentation for complex AI projects.

40% Reduction in Safety Incidents at Pilot Sites

The system delivered immediate value by significantly reducing safety incidents and improving compliance at pilot locations.

Built a Lasting Internal AI Capability

Through collaboration, the client's internal team gained the skills to manage the platform, creating a sustainable in-house AI capability for future innovation.

These results demonstrate the transformative power of AI when implemented strategically and thoughtfully.

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