Scale Your Human EffortExponentially
Compound AI is the control plane for autonomous agent networks. Every decision, approval, and strategy you provide acts as a seed—our agents learn, execute, and grow your operations exponentially, turning linear work into boundless scale.
The Recursive Self-Improving Loop
Compound AI operates on a continuous feedback architecture. Agents perceive reality, execute actions based on policies, pass quality audits, and learn to patch their own skills.
Designed For Safe, Scalable Autonomy
Compound AI wraps advanced agent capabilities inside a secure, legibility-first control architecture.
Skills, Harnesses & MCP
Import custom code actions, connect unit-test harnesses, and plug in Model Context Protocol (MCP) servers. Equips your agents with secure filesystem, database, and terminal tools.
Granular Permissions
Define precise authorization bounds. Control which directories agents can modify, which database schemas they can query, and which console commands require human approval.
Exponential Scale
Every strategy and human approval acts as a seed. Compound AI detects patterns in your workflow, converting one-off decisions into repeatable, agentic playbooks that scale infinitely.
Self-Improving Agents
Agents ingest feedback telemetry from successes and failures. The platform auto-patches agent instructions and code scripts, improving the quality of deliverables while you sleep.
Goal Decomposition & Handoff
Watch the dynamic transition. The CEO Agent sets a roadmap, breaks goals into tasks, pulls instructions from playbooks, requests human approvals, and promotes tasks to autopilot.
Declare Your Workflows in Code
Control how agents operate using clean, legible configuration playbooks. Limit write directories, restrict database schemas, and define autopilot confidence criteria.
# playbooks/caching-migration.yml
name: "Redis Caching System Migration"
description: "Sync with company caching standards and automate Redis client integration."
version: "1.0.4"
# Explicit sandbox write and execute permissions granted to executing agent
permissions:
- path: "src/services/db/"
access: "write"
- shell: "pnpm db:generate && pnpm db:migrate"
access: "execute"
# Governance parameters: confidence locks transition to autopilot execution
quality_gate:
required_approvals: 1
autopilot:
threshold: 0.95 # Bypass human review once agent confidence exceeds 95%
min_approved_runs: 10 # Minimum supervisor evaluations required firstLegibility-First Task Hierarchies
In Compound AI, initiatives flow from top-level business strategies down to granular sub-issues. Every action is tracked under a single responsible individual (FTE or Agent), eliminating ambiguity.
Clear ownership prevents diffusion of responsibility. Issues are assigned strictly to one human owner (assigneeUserId) or one agent adapter (assigneeAgentId).
Issues are cataloged via prefixes based on team namespaces, such as ENG-294 or OPS-12, for easy human communication.
ENTITIES IN WORKSPACE:
Calculate Your Operational Savings
Estimate the resource hours and margin value reclaimed by progressively transitioning repetitive roles to Compound AI agent playbooks.
Calculate Your ROI
Simulate how delegating operations to Compound AI agents impacts your resource allocation and bottom-line margins.
🤖 How this works: Instead of immediate full automation, Compound AI allows you to gradually map processes, import company playbooks, and delegate tasks to custom skills. This 60% handoff reclaims 1.1 employees' worth of bandwidth to focus on strategic growth.