Driving Engineering Excellence Through AI Innovation

Exploring AI-Driven Productivity: How ojas.design Helped a Major Engineering Firm Harness the Power of AI

At ojas.design, we believe that when innovation meets intent, extraordinary things happen. In our recent engagement with a large engineering organisation, we set out to do just that,by launching a program to explore how AI could elevate engineering quality and productivity at scale.

The Challenge: A Need for Smarter Engineering.

The client, a global player in engineering and infrastructure, faced a familiar set of modern challenges: increasing project complexity, tighter timelines, growing regulatory scrutiny, and an explosion of available data. While their teams were technically strong, much of their effort was devoted to manual tasks—repetitive data analysis, error checking, document validation, and information retrieval.

The leadership knew they needed more than incremental improvement. They needed a strategic leap—something that could unlock smarter workflows and empower their engineers to focus on what they do best: engineering.

Our Approach: Designing for Exploration, not Just Execution

Rather than starting with a single solution, ojas.design proposed a programmatic approach to AI Proof of Concept (PoC) development. Our goal was to create a structured environment where ideas could be tested, iterated, and either scaled or shelved based on real outcomes, not hype.

We co-designed a framework with the client's innovation and engineering leads, built around four key pillars:

1. Opportunity Identification: Through workshops and data audits, we identified high-potential use cases across engineering functions—ranging from design verification and root-cause analysis to document summarisation and predictive maintenance.

2. PoC Development Sprint: Each idea was run as a time-boxed sprint (4–6 weeks), where cross-functional teams of engineers, data scientists, and domain experts rapidly prototyped AI-enabled solutions using existing data and toolsets.

3. Evaluation & Learnings: We measured each PoC on clear criteria: productivity impact, error reduction, scalability, and end-user feedback. Even when a PoC didn’t succeed, we captured insights to guide future development.

4. Enablement & Integration: Successful PoCs were transitioned to pilot stages, with a roadmap for technical integration and change adoption. Meanwhile, we also delivered training and documentation to empower internal teams to lead future initiatives.

   
   

The Technologies: Leveraging the AI Stack

We leveraged a blend of cutting-edge AI and ML tools across the following platforms:

• Data Analysis & Feature Engineering using Python, Pandas, and custom-built analytics dashboards

• Machine Learning Models for classification, anomaly detection, and NLP (natural language processing)

• Generative AI Tools (including OpenAI APIs) for summarising engineering reports, generating code snippets, and aiding design iteration

• Platform Integration with Microsoft Azure ML, Databricks, and internal engineering software (e.g., CAD, PLM, and document management systems)

The Outcomes: Real-World Impact, Rapidly Delivered

Over six months, we delivered eight high-value PoCs. Highlights included:

• AI-Assisted Design Verification Tool: Reduced manual design rule checks by 75%, with zero increase in error rates.

• Document Intelligence Engine: Enabled engineers to query specifications and standards in natural language, saving hours per week in search and interpretation time.

• Predictive Failure Modelling: Early indicators of component degradation led to better maintenance decisions, preventing costly downtime.

Perhaps just as important: we shifted the organisation’s mindset around AI, from possibilities to practical exploration.

Looking Ahead: Scaling the Program

With early wins in hand, the engineering organisation has now committed to establishing an internal AI Innovation Lab, supported by governance structures and a technical knowledge base built during the program.

At ojas.design, we continue to support the journey—helping our clients build AI capabilities not just as a toolset, but as a mindset.

Are you ready to explore how AI can improve your organisation's quality and productivity?

Let’s talk about how we can build your own AI innovation program. Contact us at hello@ojas.design or visit www.ojas.design.