What Alephant Does

Alephant is the open-source Agentic Finance Gateway for AI agents and workflows.

It gives production agent systems one gateway for policy control, run tracing, cost attribution, and x402 monetization. Alephant sits between agents, members, workflows, models, tools, APIs, and paid endpoints so teams can govern what agents do, trace what happened, understand what it cost, and monetize what agents can provide.

1. Dashboard

The dashboard shows the operating picture of your agent system.

Alephant tracks both sides of agent activity:

• Spend out: model usage, token cost, tool/API spend, outbound x402 spend
• Earn in: paid endpoint revenue, x402 payments, MPP payments, endpoint margin

This turns agent operations into a clear financial view:

• Which agents are active
• Which workflows are generating usage
• Which models are driving cost
• Which endpoints are producing revenue
• Which runs are profitable or risky
• Where latency, errors, or abnormal spend appear

The goal is not just usage reporting. The goal is agent P&L visibility.

2. Govern Agent Runs

Alephant governs how agents and workflows run before they become expensive, risky, or hard to audit.

Teams can define policies for:

• Budget limits
• Rate limits
• Model allowlists
• Tool permissions
• Endpoint access
• Workflow guardrails
• Approval rules
• Hard stop, throttle, or alert behavior
• Department, member, and agent-level controls

This is broader than cost control. Alephant controls the full agent run: what models an agent can call, which tools it can access, how much it can spend, which endpoints it can invoke, and when a run should be blocked or escalated.

3. Agents

In Alephant, an agent is a first-class business entity.

When a team creates an agent, Alephant can bind it to a Virtual Key. That key becomes the agent’s controlled access token for model and API calls.

Each agent can have:

• Provider and model configuration
• Environment status, such as development or production
• Budget limits
• Rate limits
• Allowed models
• Department assignment
• Usage stats
• Cost tracking
• Activation or deactivation state

Instead of many agents sharing unmanaged API keys, Alephant gives each agent its own governed identity, policy, usage trail, and financial record.

4. Members And Workflows

Alephant is not limited to autonomous agents.

It also tracks and governs:

• Human team members using LLMs
• Internal workflows
• n8n and automation workflows
• MCP or tool-driven processes
• Department-level usage
• Workspace-level usage

Real AI usage inside a company is mixed. Some calls come from agents. Some come from employees. Some come from scheduled workflows. Some come from tools calling other tools.

Alephant gives all of them a shared gateway, policy layer, and audit trail.

5. Model Routing

Alephant provides a unified model gateway for agent and workflow calls.

Instead of wiring every agent directly to each model provider, teams can route calls through Alephant.

This supports:

• OpenAI SDK-compatible model endpoints
• Bring-your-own provider keys
• Provider key management
• Virtual Keys
• Model access control
• Cost-aware routing
• Provider and model-level usage tracking

The gateway becomes the control point between agents, workflows, policies, budgets, and LLM providers.

6. Logs And Run Tracing

Alephant records what happened during agent activity.

It can trace:

• Model calls
• Tool calls
• Workflow steps
• Token usage
• Latency
• Errors
• Policy decisions
• Cost
• Revenue
• Audit events

When something goes wrong, the team can answer:

• Which agent ran?
• Which model was used?
• Which tools were called?
• Which policy allowed or blocked the action?
• How much did it cost?
• What failed before the run completed?

Alephant turns agent execution into something observable and auditable.

7. Monetize Agent Capabilities

Alephant lets teams turn agent capabilities, workflows, or APIs into paid endpoints.

A team can:

• Create an endpoint
• Attach it to an agent capability or workflow
• Set a price per call
• Define endpoint policy
• Publish it
• Accept x402 or MPP payments
• Track revenue and margin

Typical examples include:

• Research agents
• Risk scoring endpoints
• Data enrichment workflows
• Compliance checks
• AI workflow automations
• Internal tools exposed as paid APIs

Alephant handles the control, payment challenge, revenue logging, and margin visibility.

8. Payments

Alephant separates agent spending from endpoint revenue.

It tracks:

• Incoming x402 paid calls
• Endpoint revenue
• Outbound x402 spend
• Payouts
• Wallet activity
• Revenue history
• Spend policies

An agent may spend money calling external APIs, tools, or paid endpoints. The same workspace may also earn money by exposing its own agent capability.

Alephant gives both sides a ledger.

9. Agent Finance

Alephant connects operational usage with financial outcomes.

For paid endpoints, it can show:

• Buyer revenue
• AI token cost
• External tool/API spend
• Platform fees
• Net margin
• Calls
• Success rate
• Latency

This helps teams avoid a common problem: publishing an AI endpoint that gets usage but loses money per call.

10. Security And Audit

Alephant is designed for production and enterprise agent systems.

It supports:

• Workspace roles
• Team members
• Departments
• Virtual Keys
• Provider keys
• Policy enforcement
• Audit logs
• Log export
• Data retention
• Access control

The product is built for teams that need governance, not just experimentation.

Product Areas

Summary

Alephant does four things for production AI agents and workflows:

• Routes model, tool, and API calls through one gateway.
• Governs every run with policy controls.
• Traces what happened with logs and audit records.
• Monetizes agent capabilities with paid x402 and MPP endpoints.

In short: Alephant gives AI agents and workflows rules, receipts, and revenue rails.