AI Agent Platforms: 7 Solutions for Team Collaboration

Creating an agent is no longer enough: teams are looking to share it, equip it, and integrate it into reproducible workflows. Seven platforms structure these uses, with varied collaboration models and real constraints regarding licenses, permissions, and credits. Here’s an overview of the approaches and use cases offered, with little to no coding required.

Licenses, Permissions, and Credits Condition Collective Access

Pooling agents requires technical and contractual safeguards. In Copilot Studio, access to a preview agent may be restricted to colleagues due to licensing constraints and tenant agreements. For Google Workspace, the availability of Workspace Studio depends on account eligibility and settings defined by the administrator, while personal accounts are not allowed to share workflows. At Taskade, using AI Teams requires at least a Pro subscription, with each agent response deducting credits, which can lead to excessive consumption if all agents are called upon for a simple request. Oasis limits its free plan to three seats combining humans and agents, and recommends checking room sizes, models, and integrations before committing. Dust encourages users to monitor connector coverage and source permissions and to designate a documentation manager, knowing that linking outdated content does not update it. With Lindy, it is wise to confirm integrations, actions, approval behavior, and credit usage for the intended task. Relevance AI specifies directional connections and suggests anticipating information flow, incomplete results, required tools, action limits, and credit costs. Finally, testing an end-to-end workflow, including what a colleague inherits and the cost of a complete execution, is advised before a wide deployment.

Three Approaches to Collaboration: Shared Agent, Cloned Workflow, Multi-Agent

The offerings are divided between common access to the same agent and its context, the distribution of cloned recipes, and the explicit coordination of multiple agents. Some platforms allow multiple users to work with a single agent and a shared context, while others favor copied workflows that each teammate executes independently. Multi-agent orchestration solutions chain specialized roles. In all cases, managing permissions, supervising activity, and ensuring process consistency across projects are common functions. These tools differ from generalist assistants like ChatGPT or Claude by treating the agent as a reusable team resource. Several offer visual or natural language builders to create workflows, while acknowledging that some complex integrations still require technical skills.

Office Ecosystems: Copilot Studio and Workspace Studio

In the Microsoft universe, Copilot Studio allows users to define instructions, knowledge, and tools for an agent, then publish it on channels like Microsoft Teams. Integration with Teams opens access to a large number of users, and child or connected agents cover more advanced designs. On the Google side, Workspace Studio develops workflows using templates or natural language instructions, leveraging Gmail, Chat, Drive, and other applications; for example, it is possible to program a workflow that summarizes unread emails and sends a digest to Google Chat. Sharing in this environment generates distinct copies: neither the execution history nor access to the original workflow files is transferred. Teams already embedded in Microsoft 365 or Google Workspace are encouraged to build from these ecosystems.

Shared Rooms and Internal Knowledge: Oasis and Dust

Oasis allows users and agents to gather in rooms where they can collaborate on a task, control agents, and track transfers. The solution offers both ready-to-use or customizable agents, application integrations, and the connection of local agents, while maintaining discussion, context, and work in a single space; the free plan allows for a total of three seats. Dust addresses needs related to internal knowledge management: team agents, designed for reuse, integrate with the organization’s tools and resources. A support agent built from validated documentation provides a common foundation, with administrative management of sources and features. It is noted that connecting outdated content does not update it. When coordinating work in a shared room involves both people and agents, Oasis or Dust should be prioritized.

Orchestration by Agent Teams and Shared Assistant: Taskade, Lindy, Relevance AI

Taskade combines projects, customized agents, and automation. Its AI Teams feature directs a request to an agent, a subgroup, the entire team, or an orchestrated team, and the automation step Ask Agent Team embeds this collaboration into recurring workflows, under a Pro subscription or higher with credit consumption per responding agent. Lindy presents itself as an AI employee operating through everyday business tools, suitable for recurring coordination like follow-ups via messages and calendars, without multiplying specialized agents; a shared assistant may suffice when no explicit multi-agent coordination is required. Relevance AI, with Workforce builder, connects specialized agents within a defined process, with transfers that may be mandatory or chosen by the AI. Connections are directional, which implies planning information flows and verifying required tools, action limits, and credit costs. To experiment with internally built coordination, a multi-agent research workflow is suggested.