Part of the AgentControlLayer Ecosystem

The Enterprise Agent Control Platform.

One platform to see, control, and optimize every agent across your organization—regardless of framework or team.

See Our Use Cases

Universal Control Plane

LangChainCrewAIOpenAIAnthropicMistral

Unified Agent Management

Centralize visibility and control for your entire agent fleet.

01

The Fleet Commander

See every agent across your organization in one dashboard. Know what's running, what's failing, and what needs attention.

  • Cross-framework Visibility
  • Health Monitoring
  • Resource Tracking
CENTRAL
02

The Policy Enforcer

Define policies once, apply them everywhere. Consistent governance across LangChain, CrewAI, AutoGen, and custom agents.

  • Centralized Policy Management
  • Automatic Propagation
  • Compliance by Default
03

The Cost Controller

Track token usage, API costs, and compute spend across your entire agent fleet. Set budgets and get alerts before you overspend.

  • Real-time Cost Attribution
  • Per-agent Budget Limits
  • Usage Forecasting

The Agent Sprawl Problem

Most enterprises have agents scattered across 5+ teams using 3+ frameworks. Nobody knows what's actually running.

Siloed Agents

Each team builds their own agents with their own frameworks. No central visibility means no central control.

Inconsistent Governance

Each team implements their own logging, rate limits, and error handling. Policies are enforced unevenly—or not at all.

Blind Spots

You can't secure or optimize what you can't see. Siloed agents mean siloed risk and duplicated costs.

How We Work With You

Visibility is just the start. We partner with you to turn observability into optimization.

01

Audit & Strategy

We analyze your current workflows and identify the highest-ROI opportunities for agentic automation.

02

Build & Architect

Our architects build your agents on the AgentControlLayer platform, ensuring security and scalability.

03

Deploy & Train

We deploy to production and train your team on how to manage the Human-in-the-Loop approval flows.

04

Optimize

We stay on as your AgentOps partner, reviewing logs and optimizing prompts weekly to prevent drift.

Who AgentControlLayer Is For

We focus on teams who already ship or operate agents and now need a proper AgentOps control plane.

SaaS Companies with Agent Features

Product and platform teams adding agents into their SaaS products—support bots, onboarding agents, lead routing, and other embedded workflows.

Internal AI / Platform Teams

Central teams that support multiple agent use cases across the business and need one place to control prompts, policies, and observability.

Agent & Automation Studios

Shops that build agents and workflows for clients and want to offer them as reliable, audited services instead of one-off scripts.

AgentOps Architecture, Not Just a Dashboard

Under the hood, AgentControlLayer is a full AgentOps control plane: a workflow engine, agent identity system, and observability layer that treat agents as first-class principals.

Workflow Builder with HITL

A LangGraph-powered workflow engine with schema-based IO, support for multi-agent patterns, and built-in Human-in-the-Loop nodes so you can pause, review, and resume critical steps.

  • Config-driven workflows (no string-eval logic)
  • Human review tasks and approval queues
  • Pluggable tools and external systems

Agent Identity & Versioning

Agents are treated as their own principals with permissions, histories, and versions—not just prompts in code. This aligns with emerging best practices from Google/Kaggle and others.

  • Per-agent permissions over tools and data
  • Full configuration versioning and rollback
  • Audit logs tied to agent identity

Prompt & Workflow Quality Layer

Designed to support Promptsmith-style atomic prompt boxes and AI-assisted reviews of prompts and workflows so you can continuously improve quality without losing control.

  • Structured prompt components (12-box framework)
  • Planned AI review of prompts and flows
  • Evaluation hooks for LM-as-judge pipelines

Unified Agent Management FAQ

Common questions about centralized agent control.

We're framework-agnostic. LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, and custom Python/TypeScript agents all work. If it makes API calls, we can manage it.

Define policies (rate limits, allowed tools, cost budgets, etc.) in the AgentControlPlatform UI. Policies are pushed to all connected agents via our SDK or proxy layer automatically.

Yes. AgentControlPlatform provides org-wide visibility with team-level RBAC. Admins see everything; team leads see their scope. No more scattered dashboards.

Three options: (1) Add our SDK wrapper (2 lines of code), (2) Route traffic through our proxy, or (3) Use our native integrations for popular frameworks.

AgentControlLayer: The AgentOps Control Plane for Enterprise AI

One AgentOps control plane to build, secure, and observe your agent fleet.

Development Experience

Advanced Prompt Engineering

Stop pasting strings into code. Our visual Prompt Builder UI allows you to design, test, and version complex prompts with variables, conditional logic, and model comparisons side-by-side.

  • Visual Prompt Editor
  • A/B Testing Playground
  • Version History & Rollbacks
Screenshot: Prompt Builder UIEditor with variable inputs & model output comparison
Screenshot: Agent Version ControlDashboard showing active deployments & health metrics
Security & Governance

Robust Agent Identity & Security

Treat agents as first-class citizens with their own IAM roles. Manage permissions, enforce budget limits, and maintain complete audit trails of every decision your AI makes.

  • RBAC for Agents
  • PII Redaction Middleware
  • Complete Audit Logs
Lifecycle Management

Full Lifecycle Management

Bring DevOps discipline to LLMs. Version control your entire agent configuration—workflows, prompts, and RAG settings. Implement Human-in-the-Loop (HITL) checkpoints before critical actions.

  • Configuration as Code
  • Automated Eval Pipelines
  • HITL Approval Flows
Dev
Staging
Prod

Book Your Strategy Call

Ready to deploy agents that actually work? We are accepting a limited number of enterprise clients for our Managed Agent Program. Get a custom roadmap, a dedicated AI Architect, and access to the AgentControlLayer platform.

Limited spots available for Q1 2025.