Reusable AI Operators
Create agents once, then reuse their skills across the organization
An agent is a reusable operator that combines purpose, instructions, prompts, skills, source access, allowed tools, run behavior, and outputs into something the user can run repeatedly.
Agent Blueprint
Visible access, skills, tools, and outputs
Purpose
Define the job the agent is meant to perform and the outcome it should produce.
Instructions
Give the agent durable operating rules without forcing users to manage prompt plumbing.
Skills
Attach transferable capabilities that can move with the agent across teams and workflows.
Source Access
Choose the files, systems, datasets, and knowledge the agent can use for its work.
Allowed Tools
Control the actions the agent can take, from analysis to approved integrations.
Outputs
Standardize the reports, artifacts, decisions, or handoffs the agent returns each run.
Agent Builder
Make agents understandable to the people who run them
01
Users can create useful agents without understanding internal prompt and skill plumbing.
02
Every agent shows what it can access, what it can do, and which tools are allowed.
03
Agents become the repeatable layer above chat, prompts, skills, viewer, and analysis.
Transferable Skills
Turn one working process into an organizational pattern
Create once
Package the agent's purpose, instructions, skills, model preferences, source access, run behavior, and output format into a reusable operator.
Run anywhere approved
Use hosted LLMs or local LLMs while keeping access, policy, and tool permissions visible to the organization.
Duplicate and adapt
Copy proven agents for new teams, projects, or departments while preserving the reusable skills and governance defaults that make them reliable.
Build agents your teams can understand, govern, duplicate, and reuse.
Give teams a repeatable layer for AI work while keeping model choice, local LLM use, data access, and tool permissions under organizational control.
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