Agents with ongoing roles
Create Human AIs with a defined goal, personality, model, and work mode. Delegate an outcome in plain language; the agent plans and carries out work through its available integrations.
A governed AI workforce for teams that delegate recurring research, operations, and analysis.
TESS is a workspace-based platform for creating and managing autonomous AI agents, which the company calls Human AIs. Rather than handling only single chat requests, these agents can be assigned ongoing roles and delegated outcomes in plain language. They can use selected AI models, company context, and connected tools to carry out work and report results.
The platform combines agent scheduling and execution with team organization, persistent company knowledge, approvals, and usage controls. Cowork provides a shared mission-control view for managing the AI team, while governance policies can set model, connector, context, and budget restrictions for teams or individuals. TESS is aimed at organizations that want to run AI-supported work across multiple people and workflows under centralized oversight.
Create Human AIs with a defined goal, personality, model, and work mode. Delegate an outcome in plain language; the agent plans and carries out work through its available integrations.
Set schedules and wakeups for recurring work, with a live timeline for runs. The site describes agents operating around the clock, including scheduled monitoring and reporting.
Persistent memory and connected knowledge bases provide agents with organizational context. Completed tasks can contribute to a shared living memory that agents can navigate by meaning, team, agent, or content type.
View and manage the AI workforce in a shared workspace. Cowork includes an organizational canvas, hierarchy and squads, a day planner, run history, approvals, and live collaboration.
Set restrictions by team or individual for allowed models, context size, connector access, and monthly budget. Permissions, approval gates, and audit trails support review of agent activity.
The platform lists access to more than 250 AI models, connectors, MCP plugins, an API, and integrations including Zapier and n8n. Model choice can be made per agent or run.
Assign an analyst agent to review company documents and monitor market information on a schedule, then return research findings for the team.
Use agents for repetitive operational work such as preparing reports and follow-ups, keeping staff focused on decisions that require human judgment.
Run data agents on a recurring schedule to watch a pipeline or tracked information and surface updates without requiring someone to start each run manually.
Delegate a daily team sync to an agent that can conduct a live voice meeting, record decisions, and provide a recap with action items.
Plans are priced per workspace and shared across unlimited users, rather than charged per seat. Credit allowances and pricing depend on the selected plan; Enterprise uses custom volume and engagement terms.
Credits are used for model calls, agent runs, and tool executions, with consumption depending on the model and job size. Plans include monthly credits and daily bonus credits; additional credit packs can be added. Unused monthly credits do not roll over.
Yes. Agents can be scheduled for recurring work and are described as supporting 24/7 runs. Human review can also be required through approval gates and supervised work modes.
Policies can apply to whole teams or individuals and restrict models, context size, connector access, and monthly budgets. The platform also lists permissions, approval gates, and audit trails.
Enterprise is scoped with TESS and can include custom credit volume, onboarding, Forward Deployed Engineering, SSO, advanced data privacy and compliance, priority support, and custom MSA and SLA terms.
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