Helping hospitality businesses orchestrate workflows and services using AI

Founded in 2025, Azin is an up-and-coming tech startup that helps hospitality businesses, like hotels, deliver faster, smarter services to their customers. It uses state-of-the-art AI to streamline front- and back-of-house workflows, boosting efficiency, eliminating busywork, and reducing manual data entry.

The case study explores the journey of Azin, from its initial conception to its current state, where it has secured early paying customers and revenue, and is poised for growth. It delves into the business and product strategies, discovery process, and the design and development of the Azin product.

Azin.ai helps businesses Orchestrate a Service (e.g., room service, housekeeping)—the Job-to-be-Done (JTBD). Azin started out targeting different types of industries—including Healthcare— but after market research and strategy assessment, I proposed to focus on Hospitality as the core vertical.

Through discovery sessions with staff and end-users, I helped define the JTBD of service orchestration for high-touch services—workflows requiring human interaction across multiple functions (e.g., guest check-in, room cleaning) rather than purely digital processes.

Leveraging Service Design and particularly the use of Value Stream Mapping, I synthesised complex business workflows and developed a novel approach to model and abstract these processes for reuse across businesses. This enabled us to create a scalable framework for service orchestration, and adapt to various hospitality contexts by reusing existing domain knowledge.

I established a conceptual model for the staff interface defining core elements (Work Requests, Tasks, Sub-Tasks), and built a foundational design system. I also further supported frontend development through AI-assisted tools, working with engineering to remove design/build gaps and accelerate delivery.

A significant part of my contribution was guiding stakeholders through discovery sessions with customers and guests, helping the team understand service delivery complexities and align on product strategy using the JTBD framework.

For example, our research revealed that existing automation solutions created silos with limited staff oversight. Businesses needed support for complete service journeys, from request through fulfillment, and weren't looking to add new software to their stacks. These insights directed us toward our core orchestration approach.

I further helped Azin reuse domain knowledge across businesses by introducing Work Streams , a framework that abstracts workflows for reuse while allowing customisation based on individual business needs. For example, check-in flows are similar across hotels but can vary by size and capabilities.

I also designed the product's staff-facing interface, collaborating with engineering to build foundational features and address thorny challenges like Human-In-The-Loop (HITL) collaboration. For example, we initially had two ways for humans to provide input on AI work, but realised a priority system was more effective in helping users.

Working for an early-stage startup like Azin.ai is always a challenge given the amount of uncertainty and ambiguity. However, by running a solid discovery process, I was able to help the team articulate what we were building and most importantly, why we were building it.

This enabled us to generate €230K in revenue and land 11 B2B customers in around 6 months. This was a great way to validate the problem space and the direction of the product. This further demonstrates the value of a well-defined product strategy, understanding user needs, and making constant adjustments based on signals.

Additionally, the system that I proposed to continuously engage with and test our solution with customers proved crucial. It helped us not just identify issues and validate assumptions, but also helped in addressing evolving expectations about Human-AI interaction and collaboration.