Find out about an AI-powered expertise launched at the least viable product to collect actual consumer suggestions and iterate quickly.
Once we speak about agentic AI, it’s simple to default to summary conversations about fashions, prompts, and orchestration. However probably the most compelling tales I see are those the place AI unlocks one thing deeply human—creativity, instinct, and experience—at completely new pace and scale.
That’s why I used to be excited to host Shade Meets Code: Pantone’s Agentic AI Journey on Azure, a webinar that includes two Pantone leaders, Kristijan Risteski, options architect, and Rohani Jotshi, senior director of engineering. Through the session, Kris and Rohani shared how they’re making use of agentic AI to one of the vital foundational parts of inventive work: colour—and the way an AI-ready database, Azure Cosmos DB, performs a central position in making that doable.
The problem: Scaling colour experience in a real-time, interactive world
Pantone is well known as a worldwide authority on colour. For many years, their groups have mixed human experience, colour science, and development forecasting to assist designers and types outline, talk, and management colour throughout industries—from style and product design to packaging and digital experiences.
However as Pantone defined within the webinar, translating that depth of experience into a contemporary, conversational AI expertise got here with actual challenges. Creating colour palettes is each time consuming and demanding to the design course of. Designers usually collect inspiration by navigating between instruments, colour pickers, and development studies earlier than they ever land on a usable palette.
Pantone noticed a chance to rethink that workflow completely: What if designers may work together with a long time of Pantone analysis, development information, and colour psychology by means of a chat-based interface—and generate curated palettes immediately?
Introducing the Palette Generator: An agentic AI expertise
The result’s Pantone’s Palette Generator, an AI-powered expertise launched at the least viable product to collect actual consumer suggestions and iterate quickly. Quite than providing static suggestions, the Palette Generator makes use of multiagent structure to reply dynamically to consumer intent, conversational context, and historic interactions.
Within the webinar, the Pantone workforce described how they designed the system to incorporate specialised brokers—resembling a “chief colour scientist” agent and a palette era agent—every accountable for totally different facets of reasoning, context retrieval, and response era. These brokers work collectively to ship curated colour palettes that mirror Pantone’s proprietary information and experience.
What stood out to me was not simply the sophistication of the AI, however the architectural self-discipline behind it. Agentic AI isn’t nearly fashions—it’s additionally about information.
Why Azure Cosmos DB was foundational
On the coronary heart of Pantone’s Palette Generator is Azure Cosmos DB, serving because the system’s real-time information layer. Azure Cosmos DB is used to retailer and handle chat historical past, immediate information, message collections, and consumer interplay insights—all of that are important for responsive, quick, context-aware brokers.
As we did our analysis to seek out the most effective persistence storage, we explored totally different databases. What we discovered for Azure Cosmos DB was how simple it was to combine it into our programs. We have been capable of make our preliminary proof of idea with a number of strains of code and retrieve all the info very, very quick, like in a number of milliseconds.
Kristijan Risteski
Azure Cosmos DB was additionally chosen due to its scale, permitting Pantone to serve customers all around the world with quick information retrieval.
It is a crucial level. As functions shift from “doing” to “understanding,” databases should assist excess of easy transactions. They should deal with large volumes of operational information, adapt as AI workflows evolve, and assist superior situations like conversational reminiscence, analytics, and vector-based search.
Pantone’s structure demonstrates what it means to be “AI-ready.” Azure Cosmos DB supplies the scalability and adaptability wanted to trace consumer prompts and conversations throughout classes, together with analytics that assist Pantone perceive how prospects work together with the Palette Generator over time.
From textual content to vectors—and what comes subsequent
One other perception Pantone shared through the webinar was how their structure is evolving to enhance relevance, accuracy, and contextual understanding. Whereas the present system already helps wealthy conversational experiences, the workforce outlined subsequent steps that contain transferring from conventional textual content storage to vector-based workflows. This contains embedding consumer prompts and contextual information, permitting for vector search, and enriching responses with deeper semantic understanding.
Azure Cosmos DB performs a job right here as properly, supporting vectorized information, integrating with agent orchestration, and embedding fashions deployed by means of Microsoft Foundry. This enables Pantone to iterate with out rearchitecting the whole system—a necessary functionality when working in a fast-moving AI panorama.
Actual-world outcomes from agentic structure
Pantone didn’t simply speak about imaginative and prescient—they shared concrete outcomes from actual utilization of the Palette Generator. Based on the webinar information, customers throughout greater than 140 international locations engaged with the device, producing hundreds of distinctive chats throughout the first month of launch and interacting in dozens of languages. The system noticed a number of queries per consumer session, indicating that designers have been actively experimenting, refining prompts, and exploring concepts conversationally.
Simply as importantly, Pantone emphasised how quickly they’ve been capable of study and adapt. Immediate sensitivity, consumer habits, and architectural tradeoffs round pace, value, and reliability all knowledgeable ongoing refinements. Azure Cosmos DB’s flexibility made it doable to seize these insights and evolve the expertise with out slowing innovation.
Classes for anybody constructing agentic AI
Pantone’s journey reinforces a number of classes I see repeated throughout prospects constructing AI brokers on Azure:
- Agentic AI is inherently information pushed. With out a real-time, scalable database layer, even probably the most superior fashions battle to ship constant, context-aware experiences.
- Suggestions loops matter. By capturing prompts, responses, and consumer interactions in Azure Cosmos DB, Pantone can constantly enhance each the AI and the product expertise itself.
- Flexibility is nonnegotiable. AI architectures evolve shortly—from orchestration patterns to embedding methods—and databases should evolve with them.
What Pantone has constructed with the Palette Generator is greater than a characteristic; it’s a blueprint for the way organizations can translate deep area experience into clever, agent-driven functions. By combining Microsoft Foundry, Azure AI companies, and an AI-optimized database like Azure Cosmos DB, Pantone is exhibiting how creativity and expertise can transfer ahead collectively.
As extra organizations embrace agentic AI, the query gained’t be whether or not they can deploy fashions—however whether or not their information foundations are able to assist real-time understanding, reminiscence, and scale. Pantone’s journey makes that reply clear: AI-ready functions begin with AI-ready information.