AxLoop
Agent Interaction Observability from the Edge

See how AI actually interacts with your software.

AxLoop discovers agents, models, MCPs, tools, and AI services at the edge — then maps how they connect to applications and enterprise systems.

Discover → Map → Trace → Govern

See AxLoop in action Explore the platform

Mac · Windows · iPhone & iPad · Android · Servers

Interaction trace

Agent Interaction Trace

See what happened, failed, and followed.

Live model
10:42:01
Agent detectedLocal agent
18 ms
10:42:03
Skill selectedDeploy workflow
42 ms
10:42:04
MCP invokedRepo server
86 ms
10:42:05
Tool calledwrite_file
680 ms
10:42:06
Policy checkApproval required
12 ms
10:42:08
Action recordedAudit evidence
24 ms
Failure isolated Tool call exceeded the expected response window.t + 680 ms
Illustrative trace concept · Product direction

Available now · Edge AI Discovery

Start by discovering what exists.

Before you can understand AI interactions, you need to know what is running.

  • AI applications
  • Agents
  • Coding assistants
  • Local models
  • Model runtimes
  • MCP servers
  • MCP clients
  • AI endpoints
  • AI-related processes

Applications

See installed applications and software across supported devices, beyond your approved catalog.

AI tools

Identify AI assistants, coding tools, and local AI applications operating across endpoints.

Agents

Discover supported local agents, agent runtimes, and AI processes running in your environment.

Connections

See supported MCP clients, servers, and declared tool connections.

Services

Discover background services and runtimes that are not ordinary desktop apps.

More on YouTube → @AxLoopAI

Discovery is the foundation, not the end state.

Your software is being used by agents you don't control.

A user may ask Claude, ChatGPT, Gemini, Copilot, or another AI assistant to complete a task.

The agent may select a skill, invoke an MCP tool, call an API, interact with an application, or never invoke your software at all.

Your application may see the final request. But you rarely see the interaction that produced it.

You know the API call. You don't know the story.

The blind spot

The new observability gap.

Traditional application observability starts after a request reaches your application, API, or cloud infrastructure.

But AI-mediated interactions begin earlier — on the endpoint, inside an agent, skill, model, or MCP workflow.

AxLoop starts at that edge.

The problem

The Blind Spot

Reveal the unseen path behind each request.

Live model
HumanUserIntent begins
AgentAI agentPlans the task
?Unknown interactionDecisions · skills · tools · context
ApplicationYour softwareReceives request

No visibility into agent decisions, skills, tools, or context.

Near term · AI Interaction Mapping

From inventory to interaction.

Discovering an agent is only the beginning. The next question is: what is that agent actually doing?

AxLoop is evolving from endpoint discovery into interaction observability — mapping how agents, skills, MCPs, tools, and applications connect.

Device → Agent → Skill → MCP → Tool → Application

Interaction mapping

AI Interaction Graph

Trace agents from edge to enterprise systems.

Live model
DeviceEdge deviceMac · Windows · mobile
AgentAI agentLocal or remote
SkillCapabilityWorkflow or task
MCPProtocol serverModel Context Protocol
ToolActionFunction or command
ApplicationEnterprise systemDestination
Observed evidenceMapped relationshipNot yet observed
Interaction mapping · Near-term product step

Why edge

The interaction starts before the cloud sees it.

Most observability begins when something reaches an application, API, gateway, or cloud service. AI increasingly begins somewhere else: on the device.

That is where users interact with assistants, developers run coding agents, local models execute, MCP servers operate, and agents connect to enterprise systems.

AxLoop starts there.

Edge observability

Observability starts at the edge.

Correlate AI activity at the edge.

Live model
Available nowMacNative foundation
Observed
Product directionWindowsEndpoint coverage
Product directioniPhone & iPadManaged mobile
Product directionAndroidManaged mobile
Product directionServersInfrastructure

AxLoop

Edge CollectorMetadata-first evidence
EvidenceInteraction telemetryNormalized signals
Near termTrace correlationMapped relationships
DirectionPolicy & auditGoverned outcomes

The strongest verified implementation today is native macOS discovery. Broader device coverage is on the roadmap.

Explore device coverage

Not another LLM observability platform.

Traditional AI observability usually assumes you control the agent or model stack. Increasingly, you do not.

You may control only one tool somewhere in the interaction. AxLoop is being built for that world.

Your software may be invoked by

  • Claude
  • ChatGPT
  • Gemini
  • Copilot
  • Coding agents
  • Local agents
  • Future OS-native agents

AI created a new interaction layer.

Agents can connect to tools, databases, APIs, developer environments, SaaS applications, and internal systems.

The question is no longer only: "Who is using AI?"

It is also

  • What did the agent invoke?
  • What system did it reach?
  • What happened next?

For security teams, this is the new agent attack surface: risky tool access, unapproved MCPs, and connections to sensitive systems.

Roadmap

Discover → Map → Trace → Understand → Govern → Enforce.

Discovery is available now. Mapping is the near-term step. Trace, Understand, Govern, and Enforce are roadmap capabilities — not generally available today.

  1. 01available now

    Discover

    What AI exists?

  2. 02near term

    Map

    What is connected?

  3. 03roadmap

    Trace

    What happened?

  4. 04roadmap

    Understand

    Did it work?

  5. 05roadmap

    Govern

    Should it have happened?

  6. 06roadmap

    Enforce

    What should happen next?

Governance

From visibility to control.

Turn audit evidence into better policy.

Live model
Available nowObserveUnderstand activity
Product directionEvaluateDetermine quality and risk
Product directionGovernApply enterprise rules
Product directionEnforceBlock, allow, or approve
Product directionAuditCreate evidence

Observe behavior without creating another data problem.

AxLoop is designed for enterprise environments where deployment architecture matters. Full prompt capture is not required.

Metadata-first collection

Collect the information needed to identify agents, models, MCPs, tools, and connections.

Edge processing

Classify evidence locally on the device.

Customer-controlled deployment

Run AxLoop within your environment.

Minimal data movement

Send only what your teams need.

Configurable telemetry

Decide what is exported and where.

Who it's for

One interaction layer. Many teams.

Security

Discover AI usage and emerging risk — Shadow AI, agent and MCP discovery, risky tool access, policy, and audit.

AI Platform

Understand agents, MCPs, tools, and interaction infrastructure.

Engineering

Debug how AI agents interact with software.

Product

Understand whether MCPs and AI-accessible capabilities actually work.

Governance

Build policy, auditability, and accountability around AI activity.

Shadow AI MCP discovery Agent discovery

AxLoop is building the observability layer for the agentic edge.

Discover what exists. Map what connects. Trace what happens. Govern what comes next.

See AxLoop in action Explore the platform