From using AI
to working with AI.
CrewOn AI gives AI a place in your organization: a team and an account, permissions and memory, and accountability. We build the foundation for AI to work as a member, and a workplace where people and AI work together.
The operating foundation for AI Crew. Manages identity, memory, permissions, and learning so agents can work as organization members.
A workplace where email, messaging, calendars, approvals, meetings, and notes bring people and AI Crew together.
You've invested in AI.
Why hasn't work changed?
You've added chatbots, bought copilot licenses, and connected automation tools. Individual productivity has improved, but the way your organization works has barely changed. The issue goes beyond AI's intelligence.
AI sits outside your organization
Chatbots and copilots wait for someone to open a window. People still move their output into the organization, share it, and follow up.
Today's AI forgets yesterday's lessons
Context disappears when the conversation closes. Customer history, company rules, and managers' instructions do not accumulate. AI cannot grow without retaining feedback.
You can't entrust it with work
Without roles, permission boundaries, or accountability, you cannot say who asked which AI to do what. Organizations that prioritize security and audit cannot entrust real work to it.
More tools mean more complexity
Separate AI products for each role create more data silos and permission systems, making unified organizational policy and audit impossible.
AI needs a place in your organization, not just more intelligence.
Intelligence without a team, account, permissions, memory, or accountability cannot work within an organization.
What is an AI Native company?
People need more than intelligence to work in a company. They need a team and a role, an account and a workspace, permission boundaries, memory, and a way to learn from feedback. An AI Native company gives AI all of these.
AI belongs on the org chart
Each Crew has a department, position, responsibilities, a supervising manager, an email address, and a messaging seat. Its AI identity is always clearly shown.
AI does the work. People decide.
Crew members collect information, draft, review, and organize. People focus on approvals, rejections, and direction. The system always pauses sensitive work for human review.
Every action has an owner
Records show who requested an action, on whose behalf it ran, and the evidence behind it. Audit questions can be answered at any time.
AI grows with your company
Instructions and feedback accumulate in Crew memory and shape future actions. Ways of working remain with the organization even when responsibilities change hands.
A runtime for agents,
and a workplace for everyone
Adopt either product separately, or combine them into one AI Native operating environment.
Crewon.ai
More than an agent execution engine, this runtime enables agents to work as organization members. It manages identity and permissions, roles and skills, organizational memory, and traces of every execution.
Five agent layers and the runtime behind them
Every agent uses the same five layers. The platform registers, runs, and governs thousands of agents across tenants.
Enterprise Ontology × Organization Semantic Overlay
Connects the platform's shared meaning model with each organization's business language, keeping Define, Execute, and Govern in the same context.
8 linked asset types
Knowledge · Instruction · Tool · Skill · Form · Playbook · Policy · Permission
Ontology and Overlay define organizational terms, relationships, and work assets.
Organization Semantic Overlay
Interprets intent and business context, assembling the evidence needed for execution.
Context Snapshot
Keeps verifiable records of decisions and execution evidence under policy and permission rules.
Audit · Evidence
Subscribes to and normalizes external events from email, messaging, approvals, ERP, and webhooks. Duplicate events are merged into one task.
Webhook · IMAP/SMTP · CDC
Normalized schemas · Idempotency keys
Classifies intent and creates plans. Routes work to LLMs, ML/DL models, and rule engines according to task requirements and security policies.
LLM / sLM · ML/DL classifiers · Rules
RAG evidence injection · Token budgets
Calls and connects systems through APIs, MCP, and RPA. Delegates to other agents and combines their results.
REST / gRPC · MCP · RPA
A2A delegation · Retries · Compensating transactions
Supplies evidence to all three layers.
Permission-filtered retrieval · TTL policies
Deploy after approval · Rollback
Delegated permissions, policy gates, model routing rules, and per-tenant governance profiles.
Policy Engine · Enforced four-eyes checks
Traces perception, reasoning, execution, and approval, with tamper-evident logs, cost and performance monitoring, and SIEM integration.
Hash-chained logs · SIEM export
The point for human approval, rejection, delegation, and correction. Sensitive actions must pass through this interface before execution.
Web · Mobile · Messaging approvals
CrewAI.Work
Designed from the start for people and AI Crew to be colleagues in one workspace, with email, messaging, calendars, drive, approvals, meetings, and notes working together.
Microservices for work. Events for collaboration.
Each work tool is an independently deployed service. Changes flow between services as domain events. The Crewon.ai runtime is another member subscribing to those events.
Independent store
Independent store
Independent store
Independent store
Independent store
Independent store
Permission boundaries
CDC · Webhooks
The runtime subscribes to this backbone. Perception receives events, Reasoning evaluates them, and Action & Execution calls each service's APIs and MCP interfaces. Results return to the backbone as events such as crew.reported.
Sensitive events appear as decision cards in the workspace before execution. Human approvals, rejections, delegations, and corrections become events that feed the runtime's Feedback Loop.
Crewverse
An ecosystem where experts and partners turn their expertise into AI Crew that can perform real business work, and companies and public institutions hire the capabilities they need. Usage and expert review can generate licensing and review revenue.
From expertise to building, validation, hiring, and revenue
Build, validate, and hire AI Workforce with real business capabilities, beyond buying and selling prompts.
- 01
Expertise
Define specialist knowledge and practical experience.
- 02
Build and validate
Refine AI Crew capabilities and their evidence in Crew Studio.
- 03
Hire and use
Companies and public institutions hire needed capabilities through Crew Marketplace.
- 04
Revenue
Actual usage and expert review lead to licensing and review revenue.
Crewverse is an AI Workforce ecosystem that turns expertise into real business capabilities.
People focus on decisions: approve, reject, and guide.
Crew perceives, recalls, drafts, and reports proactively.
Feedback accumulates in memory, making ways of working an organizational asset.
Start with SaaS,
or deploy on your infrastructure
Both products are available as SaaS and on-premises deployments. Choose a profile that fits your security and regulatory requirements, with the option to move later.
SaaS
Create an account and hire your Crew to get started today. Ideal for department pilots and quick validation.
On-premises
For organizations in finance, government, and manufacturing that must keep data in-house. A secure home for enterprise knowledge and a new interface to legacy systems.
“Can we give AI real authority?”
Our architecture answers the first question about adoption. These are the foundations of how the system works, not optional switches.
Knowledge access follows the requester's permissions. Recall is blocked for people who were not part of the original context.
Every action carries short-lived permissions bound to its delegator. Delegation can be revoked at any time.
The system pauses external sends and approval decisions for human review. The author and approver cannot be the same person.
Perception, reasoning, execution, and approval are recorded in a chain that makes tampering detectable.
Start small. Grow across your organization.
Becoming AI Native is a gradual journey. Start with one department and two or three Crew members, confirm results, and expand.
Assess and design
Map department events and repetitive tasks, define roles for the first Crew members, and agree on security, infrastructure, and deployment requirements.
Pilot
Hire two or three Crew members in one department and run real workflows across messaging, email, and approvals. Validate approval gates and audit controls in daily work.
Expand
Hire Crew across departments and onboard knowledge and instructions. Adapt governance policies to each department.
AI Native operations
Work centers on the AI operations console. Crew collaboration and delegation become everyday practice, and accumulated ways of working become organizational assets.
Quantitative: has work changed?
Compare initial response times, human hours spent on repetitive tasks, approval review lead times, and cases requiring human intervention before and after the pilot.
Qualitative: has trust grown?
Review how often employees delegate to Crew, how approval gates feel in practice, and feedback from audit and security teams. Expand authority only once trust is established.
CrewOn AI Inc.
We build workplaces where people and AI create greater value as one team. AI becomes each employee's best Crew member, rather than replacing them.
We do this through two products: the runtime that lets agents work as organization members, Crewon.ai, and the workplace where people and AI Crew work together, CrewAI.Work.
- Company
- CrewOn AI Inc.
- Founded
- 2026
- CEO
- Hochul Song
- Services
- Crewon.ai · CrewAI.Work — SaaS and on-premises options for each
People bring creativity.
AI adds execution.
Together as one Crew,
we create greater value.
One Crew. Infinite Possibilities.
Customer and partner logos will appear here once the logo files are provided.
Frequently asked questions
For anything else, talk to us about adoption.
No. Keep your existing systems. An AI Native operating layer sits above them, allowing Crew to respond to work events from ERP, groupware, approvals, and email and call their functions through standard interfaces. Start one department at a time without a big-bang migration.
Crew remembers who was present when a memory was formed. It does not recall that memory for someone outside that context. Access follows the requester's permissions, so documents they cannot view are also unavailable through AI.
No. Even when a Crew member has permissions, the system pauses sensitive actions such as external sends and approvals until a person approves them. Author and approver must be different; this is enforced in code.
No. Policies can combine global, Korean, and self-hosted models. For example, sensitive work can be routed only to Korean models. Changing a model means updating policy, not rebuilding the system.
Yes. SaaS, white-label, and on-premises are three standard deployment profiles. We work with you on scope and a migration roadmap based on your infrastructure and security requirements.
Yes. Each is available separately. Use the Crewon.ai runtime with your existing tools, or add CrewAI.Work when building a new workplace for people and AI.
From using AI
to working with AI.
We help plan adoption and pilots. Together, we map your organization's work events and propose roles for your first Crew members and the right deployment setup.