Chat Blu
Engineering Trust in Multi-Channel Commerce
The Project
Managing inventory across multiple channels is a huge headache for every e-commerce business. AI is a natural tool to use for syncing shop data across Shopify, Amazon and more, but with it comes a sense of unease.
ChatBlu, a new AI e-commerce platform, aimed to solve those issues and needed a brand that conveyed trust and stability, and a product that made data management clear and friendly.
We led the Creative Direction and Product Design, crafting a high-fidelity brand identity that's both approachable and authoratative and a product strategy and UX/UI for their web application that integrated chat and traditional tables and data management into a modern framework.
Our work helped push how users expect to interact with AI in a new direction, and helped ChatBlu secure $500M in pre-product funding and new partnerhips.
Deliverables
Industries
Date & Timeline
Mapping Data & Resolving Conflicts
The ChatBlu platform manages thousands of SKUs across dozens of integrations. Combining the speed of AI with the precision of traditional UX required a strategy where every automated action is both visible and reversible.
The primary bottleneck for merchants is data collision. The fear that a price change on Shopify might break an Amazon listing. We solved this through a structured onboarding process that forces a source of truth for every field.
Precise Mapping: When adding new channels, users map holistic fields and specific products. The UI surfaces conflicts immediately, offering clear, one-click resolution choices rather than making automated guesses.
Managing Density: We built a product table that handles massive data structures without overwhelming the user. By using a layered hierarchy and progressive disclosure, we allowed power users to drill into granular API configurations directly within a cell without losing their place in the catalog.
More than chat. A collaborative workspace.
Trusting AI to update a product catalog feels risky. While chat interfaces are great for context, they're not great at showing the big picture. We needed to show users exactly what was being changed so they could feel confident in the automation.
To solve this, we moved the chat out of a bubble and into a side-by-side workspace. The chat acts as an overlay with its own separate contextual canvas to show product edits or supplier orders in real-time.
Side-by-Side Validation: With the chat on the left and a structured form on the right, users can watch the AI perform edits. It makes the invisible part...visible!
The Audit Trail: Anytime ChatBlu touches data, the field is marked with a special label. Users can interact with this label to see previous values and alternative AI recommendations right in context. This ensures total reversibility and eliminates the fear of an AI making unwanted errors.
The Results
ChatBlu secured $500M in pre-product funding, followed by an influx of future investment interest and new partnerships. Early users were able to onboard quickly in Q1 2026.
The Visual Identity
AI has a specific look. It's purple, sparkly, and it doesn't exactly convey dependability. We moved away from industry trends to focus on the reality of the work.
Using the name as a starting point, we leaned into the theme of the deep ocean: a world of integrations and data that can be overwhelming without clarity.
We grounded the brand in a personified mascot: the crab. Its pincers a metaphor for the product’s ability to grip and manage disparate data sources simultaneously. We paired this with a bright blue-ocean palette and high-contrast typography to establish immediate credibility with enterprise-grade users and buck the trends of dark AI.