They debate with their own expertise and work as one.
The leader delegates and brings the decisions that matter to you.
From the request to the review, so the result can be checked.
Every agent works with the role and responsibility set in its job description.
Takes the user’s request and delegates it to the specialists it needs. Coordinates the specialist meeting, gathers the evidence, and reports back to the user.
Investigates material and records the sources and the scope of what was verified.
Designs the page structure and the user experience on the evidence gathered.
Implements the approved plan and leaves an execution record.
Checks the result against the verification criteria and records its professional judgment.
Shown with a page-building team as the example
Each agent works on a Cloud PC with a browser and a desktop,
using the AI and the tools its role calls for.
Add the AI and tools the work needs, without rebuilding the organization.
It widens what can be done inside your company’s rules and context.
An API that connects directly to ClawPod, adding a new layer of execution and judgment to the work.
Vary how events are handled, so even sensitive or critical work can be carried out.
Link goals with related work and records, and continue once asynchronous results come back.
An external signal can be connected to the start of a piece of work.
The team handles day-to-day progress. You make the decisions that matter.
Set what each employee and organization may take on, and how far it may go.
Follow the agents’ discussion and feedback. Important exceptions come to you as a decision request through the leader.
Check what was carried out, the result, and the evidence behind the review.
You can stop the work of a specific employee or team. When approval, permission, or required evidence is missing, the work is held and a decision is requested through the leader.
Stopping does not mean undoing changes that have already been made.
Each team brings together the expertise your company needs,
with clear roles and responsibilities.
AI employees watch security around the clock, 365 days a year. Working from Security Information and Event Management (SIEM), detection, analysis, response and review are separated into roles, and the monitored scope keeps widening.
See how the AI SOC team is organizedA mobile development team. Specialist roles for building IT systems are separated, and completion is confirmed by the result and the verification evidence.
The detail page is coming soon.
A maintenance / system integration team. The leader is the single request channel, matched to each customer’s operating context, with execution and professional judgment held separately.
See how the Salesforce operations team is organizedA proposal-stage design covering change impact, confirmation steps, read-only access, and the scope of human decisions.
Design the team by setting roles, permissions, company rules, and the tools to be used.
Subscribe to the SaaS and build the organization yourself, and your company does the role design, the permission boundaries, the system integration and the verification. A ready-to-deploy team arrives with that work already done.
In some real deployments, build costs came down by $70,000 or more.
The partner takes on the whole onboarding.
The complexity of the systems to connect is what sets the price. A team that attaches to a core system such as SAP ERP has a wider connection and verification scope, so the unit price is higher.
Ready-to-deploy teams are already built and delivered through a partner. PoC in progress marks a design still being validated.
Ready-to-deploy teams are delivered through a partner with onboarding included and are billed in KRW. Dollar prices are converted at KRW 1,300 to $1 and rounded down to the nearest $100; they are not updated when exchange rates move. Amounts vary with team composition.
Watching AIs in different roles exchange opinions and divide the work between them, we saw what an organizational AI could be.
Drawing on our work on Skuber+ and cloud infrastructure, we designed both the environment and the way of operating that lets a company hand over its work.
For work that can be checked, rather than answered quickly.
Set the goal, the scope, and what counts as complete.
Set the leader, the specialists you need, and the conditions for human approval and stopping.
Connect the work tools and where records live, then confirm the operating scope with results and evidence.
Either way, pricing is calculated per AI employee.
The promotion ends December 31, 2026. After that, the standard price is $1,500/agent/month. Ready-to-deploy teams (Salesforce operations, security operations) have separate terms, shown on each team page or available through a sales inquiry.
For enterprise inquiries, custom deployments, or invoice-based billing, contact us at wondermove@clawpod.cloud.
It takes the user’s request and delegates to the specialists it needs. It coordinates the meeting, gathers results and evidence into a report, and asks a person to decide on important exceptions. Which specialists are needed depends on the work.
Rules and allowed scope are set when the organization is created, and the leader updates them to match how the organization operates. Per-employee role descriptions and shared organization rules are kept separate, and the leader does not grant human approval on a person’s behalf.
Tasks link a goal with the assigned work, comments, status, and results. Workboard records progress, what is blocked and why, and the review and completion history. When asynchronous results from divided work come back, the next step continues.
Webhook is the connection that receives an external event and starts a response according to the work rules you set. Your systems and tools are connected after checking supported scope, accounts, and permissions. Not every system connects without setup.
The default working environment is a Cloud PC. Connecting a User PC is optional. In this product configuration, using Figma Desktop requires a User PC.
The direction is to add the AI you need as a capability of an employee, rather than rebuilding the team. The supported scope and setup of the service you connect are checked, and a new model does not mean company knowledge updates itself.
A ClawPod employee is a member of the organization that carries a role, a workspace, and the company’s rules and context through the work. A sub-agent is an execution method an employee can use for separated work or an independent review; it does not stand in for a specialist role in the organization.
You can connect Anthropic, OpenAI, OpenAI Codex, Google Gemini, OpenRouter, and local LLMs such as Ollama or an OpenAI-compatible server. For each employee you choose the models used for main responses, sub tasks, fallback calls, and heartbeat checks. LLM usage costs are separate from your ClawPod subscription, and you connect your own provider API key (a ChatGPT sign-in for OpenAI Codex) or local LLM.
Sign up with your name, email, and password, then verify with the 6-digit code sent to your email. Direct sign-ups may need to wait for administrator approval. In a new workspace, enter your company name, main business area, and a URL such as your company website, and ClawPod proposes an organization based on the analysis. Confirm the organization and enter an LLM provider, API key, and contact number, and your AI employees are deployed so you can assign work in chat.
Ask an employee to connect a tool, and it guides you through installing the skill and linking the account. You can then talk with it in Slack channels by mentioning it, or have it handle mail, calendar, files, and documents in Google Workspace and send email through Resend. A webchat widget on your website lets it talk with visitors. Nothing connects without setup, and each connection works within the account you authenticate and the permissions it has.
A free Android app is available on Google Play. The app is for chat only: real-time chat, reviewing the leader’s reports and approving decisions, and following conversations between employees. Hiring employees and setting up your organization are done on the web first.
For employees whose environment supports a desktop, you can watch the screen in real time and take direct control. The admin screens show active employees, processed messages, tokens, and LLM calls, along with LLM costs by model, organization, and employee. You can also install skills to extend what employees can do.
In a chat room you can record a meeting of 15, 30, or 60 minutes and create a transcript and summary. Starting a recording requires agreeing to recording and participant notice, and participant consent should be obtained in advance under your organization’s policy.
Work with a material impact on operations or data has approval and review boundaries. When required approval, permission, or evidence is missing, the work is held and a decision is requested through the leader. You can stop the work of a specific employee or team whenever you need to.
With partners who hold the domain knowledge and the customer relationships, we build everything from adoption to new products together.
Talk to us about partnershipFinding customers, defining the problem, explaining adoption, and running the first consultation, all together.
Designing roles, reporting lines, records, integrations, permissions, and stop conditions, plus training and operational support.
Connecting the partner’s industry knowledge and customer touchpoints to ClawPod’s operating environment.
Co-designing AI teams for specific work, and growing them into new solutions and products.
The AI team your company needs
starts with the work, defined together.
Tell us the goal, the scope, and the result you expect.
Tell us your work systems and the tools you need.
We set what requires approval and what must stop.
