ThoughtSpot, the Data and AI platform company, launched AgentSpot bringing Multiplayer AI to the enterprise. AgentSpot lets people and goal-based agents work side by side as a trusted AI workforce. Anyone can use natural language to build agents, automate workflows, and create interactive business applications, then share them with colleagues. Grounded in shared memory, trusted business context, and enterprise-grade governance, AgentSpot helps organizations move fast while staying in control.

Generative AI began with the chatbot: one person, one prompt, one conversation. It made individuals more productive, but real enterprise work doesn’t live in a chat window. It lives in the teams, processes, and systems that depend on each other.

Multiplayer AI changes that. In AgentSpot, people and agents create, collaborate, and execute in a shared workspace. Instead of every conversation starting from scratch, what one person builds becomes a trusted, reusable capability for the entire enterprise.

“Companies have spent billions on AI, and most still can’t show the ROI. They gave every employee a chatbot and called it a strategy. But organizations don’t win as individuals. Winning teams run on shared knowledge and coordinated action,” said Ketan Karkhanis, CEO of ThoughtSpot. “AgentSpot gives every company an AI workforce that knows its data, has shared context and memory, and works within the rules IT sets. Your business has never been single-player. Your AI shouldn’t be either.”

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The Enterprise AI Challenge: Plenty of AI, Not Enough ROI.

The problem isn’t access to AI. It’s what happens to the work. A sales rep builds an agent to research accounts. A finance analyst creates a process to investigate variances. A marketer sets up a workflow to track competitors. Almost none of it leaves the person who built it, so the rep on the next team builds the same agent again, and the analyst in another region never learns the process exists.

Meanwhile, people email HTML files and PDFs back and forth, copy information between AI tools, re-explain business context, and rebuild capabilities that already exist elsewhere in the company.

That’s single-player AI: lots of activity, very little that compounds.

AgentSpot’s Multiplayer AI platform changes this. People and agents work in a shared environment, business context carries across every task, and the best agents, workflows, and applications become reusable company assets. Expertise no longer lives with the one person who built it. Teams build on each other’s work, improve what already exists, and turn individual wins into systems the whole business runs on.

Your Best People, Multiplied

The best ideas come from the people closest to the work, not a central AI team. From sales and finance to HR, legal, marketing and operations, now every team can build AI solutions by describing what they need in plain language. No code required.

Most AI tools let you share an answer. AgentSpot lets you share the process, the capability and the outcome.

AgentSpot brings together three building blocks:

• Agents are AI teammates. Describe the job, and AgentSpot builds an agent with the right instructions, business context and tools. Agents investigate questions, analyze data, recommend next steps and take action within their permissions.
• Workflows automate recurring work. Routine tasks run on a schedule or trigger, from weekly sales forecasts to financial monitoring and employee onboarding.
• Apps bring data and action together. Build live, interactive apps from a prompt, combining data from connected systems with agent-powered actions. Everyone sees only what they’re authorized to see.

Your top sales rep builds an account research agent, and the whole sales team starts using it. One analyst creates a variance workflow, and every business unit runs it. Expertise that used to stay with one person now benefits the entire company.

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Guardrails, Not Roadblocks

AgentSpot’s trust layer lets every team build and share AI, with security and governance designed from day one. Permissions ensure people see only the data they’re authorized to access. Always-on audit trails mean every action an agent takes is logged, so you can see what was done, when, and on whose behalf. Employees move fast. IT stays in control.

Grounded in Your Data

AI doesn’t fail because it can’t find your data. It fails because it doesn’t know what your data means. “Revenue,” “active customer,” and “at-risk account” are defined differently at every company, and foundation models have no way to know your versions. When two agents read the same metric differently, you get conflicting answers and actions you can’t trust.

AgentSpot is built on ThoughtSpot’s semantic layer, more than a decade of work making enterprise data understandable. Agents, workflows and apps use the definitions your business already has. When an agent acts, it acts on your data, not on a guess.

Memory That Compounds

Memory is what turns individual AI activity into lasting organizational knowledge. In AgentSpot, work doesn’t disappear into a chat history. It accumulates, so agents get smarter, answers get more relevant, and no one has to start over. Memory works at four layers, from what the whole company knows to what each person has done with each agent:

• Company memory gives every agent and workflow the same understanding of the business. Administrators set the key facts, and it grows from agent conversations over time.
• Agent memory lets creators refine how an agent works, and every improvement reaches everyone who uses it.
• User memory learns each person’s preferences, so answers get more relevant over time.
• Agent-user memory keeps each person’s history with a specific agent, so no one has to repeat themselves.