APPROACH
A proven framework for translating deep technical expertise into measurable business impact. Combining over 20 years of hands-on experience with the executive acumen needed to drive sustainable growth.
Developing clear, actionable strategies that align technology initiatives with core business objectives. Every investment is architected to drive long-term value and secure a durable competitive advantage for the enterprise.
Expertise in moving organizations beyond the proof-of-concept stage by operationalizing AI/ML solutions at enterprise scale. The focus is on building robust, reliable, and impactful systems ready for real-world deployment.
Moving beyond technical metrics to concentrate on what matters most: delivering measurable business impact. This includes revenue growth, operational efficiency, and an enhanced market position.
A proven ability to build and mentor world-class engineering teams. Fostering a culture of innovation, accountability, and excellence is key to attracting and retaining top-tier talent.
Translating complex technical concepts into clear business language. This enables executive teams and boards to make informed, confident decisions in a rapidly evolving technology landscape.
Providing forward-looking analysis on emerging trends in AI and cloud infrastructure. This helps organizations anticipate market shifts, mitigate risks, and seize future opportunities with confidence.
" Focussed, Technologist, Go-Getter, Team player is how I would describe Rajat. He is a thought leader who is ready to take tasks to completion with a smile. True asset to any team he joins. "
Vidya Laxman
Technology Director at Tesco
" Rajat has done excellent work for Tesco over the last year. He has been great to work with and is highly skilled. I wouldnt hesitate to recommend him to anyone.. "
Jon Higgins
CTO & CPO at Wehkamp Retail Group
" Rajat is highly motivated, very strong technically and a well regarded member of our department. He has a strong vision for how our department should operate technically and has helped to guide us towards that vision over the past year or so. Safe to say he's also a great guy! "
Tara Hamilton-Whitake
CEO | Founder - Inquisitive
This post contrasts the switching technologies of NVIDIA and Google's TPUs. Understanding their different approaches is key to matching modern AI workloads, which demand heavy data movement, to the optimal hardware.
It's not just about specs. This post breaks down the core trade-off between the GPU's versatile power and the TPU's hyper-efficient, specialized design for AI workloads.
A guide for technology executives on how to move beyond proofs-of-concept and realize sustainable, transformative value from agentic AI by focusing on business-first strategies.
Large-scale recommendation models involve a two-part process. First, a "sparse lookup" phase retrieves data from memory, a task that is challenging for standard GPUs. Second, a "dense computation" phase handles intense calculations, where GPUs perform well. This disparity creates a performance bottleneck. Google's TPUs address this with a specialized SparseCore processor, specifically designed for the lookup phase. By optimizing for both memory-intensive lookups and heavy computations, this integrated architecture provides superior performance for large-scale models.