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The Wand products

The workforce.
The platform.

Autonomous AI workers. The operating system for humans and agents. Together, a new foundation for how an organization works.

Wand Agents Wand OS
Individual agency.
Organizational intelligence.

Two products. One organization.

Great workers need
a place to work.

Wand Agents perform the work. Wand OS is the platform that gives people and agents a shared organizational structure, coordinated processes, and a common standard of performance.

01 / The workforce

Wand Agents

Autonomous AI workers with continuing responsibilities and the capacity to develop.

Assign a role and an outcome. Give the agent the context, access and authority it needs. It can initiate work, reason through uncertainty, use connected systems, collaborate with colleagues, and verify what its actions achieved.

Its working life continues across assignments. Relevant experience becomes a resource for the next decision—and a basis for developing better methods.

Explore Wand Agents

Intelligence with continuity

The models advance.
The organization
keeps its experience.

A worker’s identity, mandate and accumulated operating experience belong to the wider Wand architecture. They can persist as models improve, resource choices change, and new capabilities become available.

The organization develops knowledge about its own work: which exceptions matter, which strategies succeed, and where human judgment belongs. That continuity gives advances in intelligence a durable place to create value.

Model independence

Any approved model.
Guided by experience.

Every running step uses a model. The agent chooses from the models available in its garden, then learns from the outcome. As it understands the work’s patterns, it improves the choice—balancing quality, cost and speed for that specific task.

One agent. A model selected for every step.Illustrative model garden
Wand AgentIdentity · authority · experienceEvidence begins to accumulate
Available model gardenDeepSeekDeepSeek-V4-ProSelected for this step · agent runningChosen for this task before a recurring pattern is established.
  • AnthropicClaude Opus 5.5
  • OpenAIGPT-6 Astra
  • AnthropicClaude Haiku 5.5
  • DeepSeekDeepSeek-V4-Pro
  • Moonshot AIKimi K3
  • GoogleGemini 3.8 Flash

First encounter

Establish the route.

The agent selects DeepSeek-V4-Pro from its available garden and runs the task. It records the method, outcome and resources used, building evidence for the next choice.

Task assessedMethod recordedOutcome observed

A better method changes demand

Experience is an economic asset.

A recurring exception may initially require investigation across several systems. A validated strategy can make the next occurrence more direct: retrieve the method, establish that its conditions hold, act within authority, and verify the result. Novel or consequential cases can still justify deeper reasoning.

The next task can be different

A fresh case earns a fresh choice.

A changing goal, unfamiliar exception or new constraint can make a previous choice less useful. The agent reassesses its available models against the current work, then observes the result. Each outcome adds evidence for choosing well when that pattern appears again.

The economics of AI labor

Optimize for
work that matters.

The objective is useful work delivered with the right quality, speed and cost. Assess the output, the human intervention it required, and the total resources consumed to achieve an accepted result.

01

Productive capacity

Agent Runtime Hours measure the autonomous agent capacity consumed by an operation. Increase that capacity as more responsibilities move to the workforce. Its value depends on the work, the systems, the mandate and the outcomes achieved.

02

Compounding efficiency

A better operating strategy can reduce repeated investigation. Better resource selection can avoid unnecessary model cost. Track the combined effect through accepted quality, autonomous completion, latency, intervention and total cost per outcome.

03

Measured business value

Establish what the current process delivers, with its review effort, elapsed time and total cost. Compare equivalent outcomes as agents take on the work, including integration and operating costs. The return comes from a better business result.

Put intelligence
to work.

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