Arjun Mehta
Designs scalable AI architectures, LLM applications, RAG systems, and autonomous agents, and turns a business requirement into a system that can actually run.
LLMs, AI agents, RAG, Python, LangChain, vector databases, AWS
The core leadership behind GreyScript Technologies' enterprise mobile engagements, now driving excellence in applied AI.
The two people who lead GreyScript AI.
Gagan transitioned from leading enterprise-scale software initiatives within global MNC environments to building a focused, boutique organization designed for strategic growth. He brings an enterprise legacy into a high-performance setting where precision and accountability remain non-negotiable.
His leadership is partnership-first, prioritizing long-term value over short-term wins. Equally central to his vision is a people-centric culture. By cultivating a thriving environment, he ensures the team is empowered to excel because a strong internal culture directly drives client success.
Dhairya represents what modern technical leadership should be. More than a technologist, he acts as the bridge between complex business problems and elegant, scalable solutions. His philosophy is clear: technology must serve the business objective, never overshadow it.
As a mentor and guardian of code quality, he upholds architectural integrity across every project. Under his leadership, every system is engineered to be secure, scalable, and future-proof, not just functional. Leadership at GreyScript is about setting the standards that define how we build, partner, and grow.
The people who design and build the systems, alongside the two founders.
Designs scalable AI architectures, LLM applications, RAG systems, and autonomous agents, and turns a business requirement into a system that can actually run.
LLMs, AI agents, RAG, Python, LangChain, vector databases, AWS
Connects models, APIs, databases, and business tools into workflows that run end to end.
Automation, n8n, API integration, Node.js, Python
Builds machine learning and computer vision systems: image understanding, OCR, document processing, and visual recognition.
Computer vision, OCR, deep learning, PyTorch, TensorFlow
Turns a complex product into an interface people can use: journeys, design systems, and the final screens.
UI/UX, Figma, design systems, user research, prototyping
Builds the interface from the design, including layout, interaction, and the motion that makes it feel finished.
React, Next.js, TypeScript, Tailwind CSS, Figma
Builds the APIs, databases, auth, and cloud setup that an AI product sits on.
Node.js, Python, TypeScript, PostgreSQL, AWS
Turns datasets into something a team can act on: pipelines, predictive models, and the reporting around them.
Machine learning, data engineering, Python, SQL
Works out where AI is actually worth doing, and how it fits the way the business already runs.
AI strategy, process design, solution architecture
Ships the product around the model: the interface, the API, and the data store.
Next.js, React, Node.js, Python, PostgreSQL
Tests new model capabilities and keeps only what is worth putting into a product.
Model evaluation, agentic systems, prototyping
30-minute scoping call. No deck, just questions.