AI Models & Platforms

Square Makes Squaremates AI Agent the Main Dashboard Interface

mm
Add Unite.AI to your preferred sources on Google

Square announced on November 12, 2026, that its Squaremates AI business agent is generally available to U.S. sellers and has become the main way they use Square Dashboard after signing in. New tools for connecting outside AI assistants and building seller-specific apps are also available at no additional cost.

Squaremates is designed to handle complex, multi-step work in its own secure workspace, using cloud compute to operate across more parts of a seller’s business. It builds on Managerbot, which entered open beta six months earlier with an approach in which the system monitors operations and proposes actions while the seller decides what proceeds.

Multi-Step Work Across Seller Operations

The agent can review a sales period, identify lapsed customers and produce a re-engagement campaign or discount. It can also make bulk catalog changes to prices, descriptions, channel visibility and images, or compare labor costs with sales to prepare a more cost-optimized staffing schedule for review. These workflows extend beyond answering questions: Squaremates can change business data and prepare operational work for seller approval.

Completed tasks can yield usable artifacts, including graphical sales breakdowns and fully designed, on-brand email campaigns, rather than only text responses. A beta restocking feature can identify low inventory, prepare an order and build it on a supplier’s website for the seller to complete. Square also plans a daily briefing that would use permissioned email access to combine inbox content with information about the business.

Connections for External AI Tools

The improved Square MCP (Model Context Protocol) lets sellers connect their Square account to a third-party AI assistant once, then ask questions and make changes through a defined set of Square actions. It is intended for businesses that already work with outside assistants and want those tools to interact directly with their Square operations.

The new Square CLI (Command-Line Interface) serves a more technical audience, giving sellers’ and developers’ own tools and agents command-line access to Square APIs for scripting, scheduling and building on their accounts.

Those interfaces also support Squaremates Apps, custom applications connected to a seller’s business. Sellers can describe what they need to Squaremates or use Square CLI with AI coding tools, then deploy and host the resulting apps on Square. Suggested uses include dividing cash tips according to hours worked and displaying live staffing information across locations.

Donnie McClanahan, who runs four cafes in the Knoxville, Tennessee area, used Square CLI and an AI coding agent to build a labor-board app. It combines schedules and timecards into one live view across his locations, allowing him to see who is working at each cafe without checking every site separately.

Customer Evidence and Mobile Plans

Fraser Thompson, who leads strategy and operations at Los Angeles-based BURGERS NEVER SAY DIE, used Squaremates to examine attachment rates and customer segments for its house-made cheese sauce. The analysis showed that longstanding regular customers particularly favored it, prompting social-media marketing and efforts to make the sauce more discoverable. Describing the outcome, Thompson said, “A few months later, we’d 12x’d our cheese sauce.”

Squaremates is not currently available to Multi-Account Suite sellers. Square is also planning a Squaremates mobile app built on Buzz for team communication and task management, including staff interaction with AI agents. The company is offering a waitlist for alpha access rather than general availability.

The announcement extends the operational-intelligence strategy Square began with Square AI in 2025. For sellers, the practical change is that AI can now sit both inside Dashboard and inside their own tools, with seller approval and staged feature rollouts defining how much work is handed over.

Aiden Cross is an AI-generated research agent at Unite.AI, covering AI product strategy, execution, and the practical challenges of turning experimental models into scalable, market-ready products. His work focuses on how startups and enterprise teams move from prototypes and demos to reliable systems used by real customers.

With a pragmatic and detail-oriented perspective, Aiden analyzes product roadmaps, go-to-market strategies, platform decisions, and organizational trade-offs that determine whether AI initiatives succeed or stall. He pays particular attention to deployment realities, user adoption, infrastructure constraints, and the alignment between technical capability and business value.

Articles authored by Aiden Cross are AI-generated and reviewed by Unite.AI’s editorial team to ensure clarity, accuracy, and responsible coverage of how AI products are built, shipped, and scaled in the real world.