AI agent platform
An AI agent platform is only as good as what the agent knows.
Most agent platforms give you a loop and a tool list. That gets a demo working and then stalls, because the hard part is not the loop — it is the context the agent brings to each run, the capabilities it can reuse, and knowing what those capabilities are allowed to do.
Available now
Composer, public Guard scans, workspace records, policy, activity metadata and scoped keys.
Preview
Skill and Agent execution, Memory retrieval, schedules, publishing, billing and unified execution.
Context
What people usually mean
Searches for an agent platform tend to come from one of three places. They need very different things, and a platform that only serves the first will disappoint the other two.
“I have a repetitive task and want it to run without me” — this needs scheduling, memory and a reliable output shape, not a chat window.
“I built an agent in a notebook and now it has to run in production” — this needs credits, limits, audit, versioning and a kill switch.
“I want to give my team AI that knows our business” — this needs private knowledge, access control and governance more than it needs another model.
Evaluation
What to check before you commit
These are the questions that separate a platform you keep from a platform you rebuild off in six months.
Can you change model without rewriting?
If the agent definition names one provider in a dozen places, you are locked in. Model choice should be one field with a mode: fixed, recommended, auto, user choice or compare.
Does context persist between runs?
The current workspace persists collection and source records. Indexing, retrieval, citations and Agent use of that context remain planned.
Are capabilities reusable across agents?
A prompt pasted into four agents drifts into four different prompts. A versioned Skill installed by four agents does not.
Do you know what a capability may do?
Declared permissions, shown before install and enforced at run time — plus a scanner that reports what the code actually does.
Can a business process pin a version?
A prompt improvement that silently changes a compliance output is an incident, not an upgrade.
Is there a run history you can audit?
Composer and Guard can save bounded outcome metadata when enabled. Agent run history, Skill calls, Memory retrieval, billing and full result history are not implemented.
GenCMS
How the current workspace and roadmap address it
Tenant-scoped Skill install records, Memory collections and sources, Agent/Workflow/App drafts, activity policy and scoped API keys persist today. Skill and Agent execution, Memory retrieval, schedules and publishing remain on the roadmap.
Agents
Create and persist tenant-scoped Agent draft configurations. Scheduling, Agent runs and Agent run history are not implemented.
See Agents →Memory
Persist collections, supplied text and source records. GenCMS does not yet index, retrieve or cite those sources for a run.
See Memory →Skills
Save versioned install records with declared permissions and status. The Skill package runtime and marketplace publishing are not implemented.
Browse Skills →Guard
Run static analysis over a public GitHub repository or pasted package, configuration or tool text. Signed-in workspaces can save scan metadata when enabled.
Run a scan →Questions
Asked before you commit.
Is GenCMS tied to one AI provider?
The current tenant contract is region-locked to AIHK or AICA and Composer uses its chat alias. Outside-provider switching and broader Skill or Agent model routing remain product previews.
Can an agent use my company's documents?
Not yet. You can store tenant-scoped Memory collections, supplied text and source records today, but GenCMS does not index or retrieve those sources for Agent runs, and collection grants are not enforced.
How are agent runs billed?
They are not billed today because scheduled Agent execution and paid checkout are not connected. Plans and unified credits shown on the site are preview packaging.
What stops a third-party capability doing something unexpected?
Public GenCMS Guard scans report observed code and instruction signals, and a workspace Skill install record can store declared permissions and enabled status. Skill execution, runtime permission enforcement and automatic marketplace scanning are planned.
Start with the connected workspace, then inspect the roadmap.
Use Composer and Guard, persist workspace records and policies, then review the execution and retrieval layers still in development.
GenCMS is a product of IGEARS TECHNOLOGY LIMITED. Guard results describe observed signals, not guarantees.