E
Executive AI
Now accepting early access requests

Executive-level control
over AI agents

The management layer for autonomous AI. Delegate tasks, control memory and context, govern tool access—reliably execute complex workflows at scale.

Request AccessView Architecture
Memory governance
Tool permissioning
Full observability

The Problem

Current AI agents weren't built for real work

Most agent frameworks optimize for demos, not production. They break down when you need consistent, auditable execution across complex workflows.

Context bloat

Agents lose track of what matters. Unbounded context windows lead to hallucinations, missed details, and degraded performance over long sessions.

Lack of control

No visibility into agent decisions. No ability to constrain behavior, limit tool access, or enforce execution boundaries when things go wrong.

Poor reliability

Single-agent systems fail silently. No retry logic, no task handoff, no way to recover from partial failures in multi-step workflows.

The Solution

An executive layer for AI infrastructure

Executive AI sits above your specialized agents. It understands goals, decomposes tasks, assigns work, and maintains oversight—like a technical lead for your AI workforce.

EXECUTIVE LAYER

Executive AI Agent

Goal understanding • Task decomposition • Agent coordination • Quality assurance

DELEGATES TO
AGENT

Code Agent

Writes, reviews, and refactors code

AGENT

Research Agent

Gathers and synthesizes information

AGENT

Data Agent

Queries, transforms, and analyzes data

AGENT

Ops Agent

Executes operational workflows

Governance Layer

Memory Control

Scoped, persistent memory per agent

Context Management

Explicit context passing and pruning

Tool Governance

Dynamic permissions and rate limits

How It Works

Five-stage execution pipeline

Every workflow follows a predictable, observable pattern from goal to completion.

01

Understand goal

Executive AI receives a high-level objective and analyzes requirements, constraints, and success criteria.

02

Decompose tasks

The goal is broken into discrete, assignable tasks with clear dependencies and execution order.

03

Assign agents

Each task is routed to the most capable specialized agent based on requirements and current load.

04

Control memory & tools

Agents receive scoped context and explicit tool permissions. No more than what's needed for the task.

05

Evaluate & iterate

Results are validated against success criteria. Failed tasks retry with adjusted parameters or escalate.

Capabilities

Infrastructure-grade AI operations

The primitives you need to run AI agents in production environments with confidence.

Hierarchical agent management

Define agent hierarchies with clear delegation paths. Executives supervise specialists, specialists can spawn sub-agents for complex subtasks.

Explicit memory control

Agents operate with scoped, persistent memory. Control what each agent remembers, forgets, and can access across sessions.

Dynamic tool permissioning

Grant and revoke tool access at runtime. Enforce rate limits, audit usage, and sandbox dangerous operations.

Long-horizon task reliability

Built for workflows that span hours or days. Checkpoint progress, handle interruptions, and resume without data loss.

Full execution trace & observability

Every decision, tool call, and agent interaction is logged. Debug failures, audit behavior, and optimize performance.

Structured output validation

Define expected output schemas. Agents are constrained to produce valid, parseable results that integrate cleanly with your systems.

Use Cases

Built for your most complex workflows

Executive AI handles the coordination layer so your teams can focus on high-value decisions.

Software engineering workflows

From feature requests to deployed code. Executive AI coordinates planning, implementation, testing, and deployment agents across your entire development pipeline.

Example workflows

  • Automated PR review and feedback incorporation
  • Cross-repo refactoring with dependency analysis
  • Bug triage, reproduction, and fix generation
  • Documentation generation and maintenance

Research & analysis

Deep research across large information spaces. Specialized agents handle data gathering, synthesis, and structured output generation with full source attribution.

Example workflows

  • Competitive intelligence and market analysis
  • Technical due diligence on vendors and tools
  • Literature reviews with citation management
  • Data extraction from unstructured sources

Internal operations automation

Reliable execution of repetitive operational tasks. Define once, run continuously with monitoring, alerting, and human-in-the-loop escalation.

Example workflows

  • Onboarding workflow automation
  • Vendor management and procurement
  • Compliance monitoring and reporting
  • Cross-system data synchronization

Why It's Different

A management layer, not just orchestration

Most agent frameworks chain prompts together. Executive AI provides the governance, control, and reliability infrastructure that production workloads require.

Aspect
Typical Agents
Executive AI
Architecture
Single agent with ever-growing context
Hierarchical agents with scoped context per task
Memory
Unbounded conversation history
Explicit memory control with persistence policies
Tool Access
All tools available to all calls
Dynamic permissioning based on task requirements
Failure Handling
Retry the entire workflow
Checkpoint, isolate, and retry failed subtasks
Observability
Black box decision making
Full trace of every decision and action
Control
Hope the prompt works
Explicit constraints, validation, and escalation

Early Access

Ready to bring executive control to your AI infrastructure?

We're onboarding engineering and operations teams who need reliable, auditable AI agent execution. Request access to join the private beta.

No credit card required • Private beta • SOC 2 compliant