Technology
Queen Bee

Stop hardcoding brittle workflows. Define your outcomes and let the Queen Bee architect, deploy, and evolve your autonomous agent swarm.

The Outcome-Driven Development Engine (ODD)

Stop testing if your code runs - start validating if your problem is solved. Aden's ODD engine uses recursive goal-alignment to ensure your agents deliver outcomes, not just API calls.

Adaptive Worker Swarm

Deploy a "Hive" of agents that don't just follow scripts—they think in outcomes. Every worker is a self-adapting node capable of refactoring its own execution path to bypass obstacles that break traditional linear chains.

Filesystem Memory & State Layer

Move beyond volatile context windows. Aden provides a native filesystem abstraction that treats memory as a structured, searchable, and persistent environment. Give your agents the ability to read, write, and refactor their own state across workspaces and sessions.

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Agentic Cost Control (ACC) Unit Economic Tracking (UET) Traceability & Audit (TA) Deployment & Infrastructure (DI)
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The “Agentic” SaaS The Vertical AI Wrapper Regulated AI Multi-Model Platform Builders
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Insights, updates, and industry trends.

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Alpha Vantage Snapi Lextract AI
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Seamlessly connect your favorite tools.

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Technology
Queen Bee
The Outcome-Driven Development Engine (ODD)
Adaptive Worker Swarm
Filesystem Memory & State Layer
DocumentationPricing
Resources
Services
Agentic Cost Control (ACC)Unit Economic Tracking (UET)Traceability & Audit (TA)Deployment & Infrastructure (DI)
Customer
The “Agentic” SaaSThe Vertical AI WrapperRegulated AIMulti-Model Platform Builders
Blog
Case Studies
Alpha VantageSnapiLextract AI
Integrations
Developer Tools
Security Program
Careers
Partners
GitHub Discord

Adaptive Worker Swarm

Deploy a "Hive" of agents that don't just follow scripts—they think in outcomes. Every worker is a self-adapting node capable of refactoring its own execution path to bypass obstacles that break traditional linear chains.

Zero

Pre-defined Static Edges

100%

SDK-Wrapped Autonomy

∞

Horizontal Scaling

Real - Time

Logic Refactoring

Problem & Solution

The Flowchart Bottleneck

Stop Building "Puppet" Agents

Most multi-agent systems use rigid directed acyclic graphs (DAGs). If a real-world response doesn't fit a pre-drawn line, the agent fails or loops. This "linear bloat" makes production scaling nearly impossible.

Problem & Solution

Dynamic Node Synthesis

Adaptive Edges, Not Hardcoded Lines

Aden workers don't have hardcoded "next steps." Instead, the Queen Bee provides a goal-based logic that allows agents to discover and create edges on the fly. If a worker hits a wall, it can autonomously request a logic update or "evolve" its node to bypass the friction.

Problem & Solution

Resilience by Default

Self-Healing Swarms

Every worker is instrumented to detect semantic and logical failures. When a node realizes it cannot reach the goal, it triggers the Eval-to-Evolution loop, allowing the Hive to refactor and redeploy without human developer intervention.

Module

Architect, Deploy, & Evolve Autonomous Swarms

Stop hardcoding brittle workflows. Aden uses a recursive, outcome-driven engine to synthesize agent logic from natural language goals. Build reliable workforces that self-correct and improve with every execution.

Queen Bee

Learn more

Outcome-Driven Development (ODD)

Learn more

Filesystem Memory & State Layer

Learn more

Join the community of developers killing the "linear era" of AI. Deploy the Hive today.

How It Works

The Execution Engine for High-Agency Swarms

The complete infrastructure to deploy, audit, and evolve your AI workforce. Move from brittle, manual chains to validated, self-healing outcomes.

Node Generation:

The Queen Bee synthesizes worker agents based on the Goal Ob

Autonomous Discovery

Workers use Node Discovery Tools to find the most efficient path to the outcome, ignoring rigid programmatic edges.

Real-Time Monitoring

Decisions are streamed via WebSockets to the dashboard, providing an "Audit Trail" of every logic jump and tool use.

Recursive Evolution

If an agent fails semantically (e.g., missed intent), it records the failure logic and triggers a code evolution for the entire node.

The Execution Engine for High-Agency Swarms

The complete infrastructure to deploy, audit, and evolve your AI agent workforce. Move from brittle code to validated outcomes.