AgentShelf Starter
Begin with one platform user, one AI Front Desk agent, and its dedicated workspace.
Explore AI Front DeskAgentShelf AI operations platform
Put AI to work across your business without code or uncontrolled LLM spend.
AgentShelf gives businesses one place for individual agents, approved context, business surfaces, usage visibility, budget policies, and reusable workflows.
AgentShelfAI operations workflow
Live01Build
Agent instructions and approved context
02Deploy
Website, workspace, and API
03Govern
Budget, access, and usage traces
04Reuse
Shared workflow library
Governed activity
Lead capturedPolicy passedUsage recordedSaved for reuse
Active channels3
Applied policies8
Reusable workflows6
No-code agent builderApproved context and toolsUsage and cost governanceWebsite, workspace, and embedded experiences
Why now
AI is moving from experiments to a real operating expense.
Teams are adopting point tools, browser chats, custom bots, and one-off agent builds faster than leaders can govern usage, cost, access, and results. AgentShelf turns that sprawl into reusable business AI operations.
- Fragmented tools create duplicated agent builds and inconsistent answers.
- Unmanaged model access makes spend hard to attribute or control.
- Useful workflows get trapped in one tool instead of becoming reusable assets.
How AgentShelf works
One agent. One workspace. Everything it needs for useful work.
Visitors see the AI Front Desk. Behind it, a dedicated workspace keeps the agent’s instructions, approved context, tools, model access, usage, and controls together.
AgentShelf Control PlaneShared across the platform
01Where the agent works
The places where customers and users experience the agent.
02Build and reuse
Turn a defined job into a specialist, then reuse effective patterns.
03What makes the agent useful
The practical pieces around the model that prepare an agent for its job.
04Knowledge and action
Approved resources that help the agent move beyond generic answers.
05Managed execution
Shared services run supported experiences and return useful results.
Cross-cutting controlsGovernance & AI economics
Where to start
Start with the fastest use case, then expand into governed workflows.
Individual Agent Workspaces
Give one user one agent with approved company context, structured outputs, and repeatable handoffs.
Explore enterpriseBuilder Platform
Launch agentic workflows without rebuilding runtime, context, connectors, billing, libraries, and governance.
Explore builder platformCost governance
Control AI usage before it becomes invisible operating spend.
AgentShelf supports accountable model access and usage with visibility, configured budget policies, attribution, and billing records tied to the workflows creating value.
Explore cost governanceBudgetConfigured
GatewayGoverned
TraceAttributed
Usage map
Models, users, individual agents, dedicated workspaces, and deployment surfaces.
Budget policies
Configure spend limits and review the resulting budget signals where supported.
LLM gateway
Use configured provider and model access through one managed control layer.
Value attribution
Tie tokens, cost, and workflow value together.
Agent operations
Builders create agents. Operators keep control.
AgentShelf gives founders, agencies, and builders the infrastructure needed to create, connect, deploy, and manage agent workflows without rebuilding the surrounding platform.
Agent Builder
Define specialist agents, context, instructions, and reusable workflow patterns.
Deployment Surfaces
Use widgets, APIs, SDKs, dedicated workspaces, and supported external sessions.
Connectors
Connect agents to business systems, automation, and structured handoffs.
Libraries
Find and reuse approved agent patterns through the Agent Library.
Trust and operations
Built for public-facing and private business AI boundaries.
Public/private boundaries
Separate website-safe behavior from private workspace context and admin-controlled access.
Observability
Review request traces, tool calls, token usage, model/provider details, and cost signals.
Admin control
Preserve control over model access, budgets, agent availability, and workspace rollout.
Ready to turn your first AI workflow into an operating capability?
Start with a scoped conversation about the agents, governance, and rollout path your business needs.