About Frameworks Lab
Frameworks Lab is an infrastructure layer for AI agents and autonomous systems. Instead of building isolated bots, teams plug their existing agents into a shared routing framework that understands intent, risk, and context.
We act as the nervous system for your automation stack: aggregating signals, enforcing constraints, and orchestrating execution across multiple agents and tools.
- Unify existing bots and agents
- Centralize routing, approvals, and constraints
- Log behavior and outcomes for continuous improvement
Architecture
Input
Market data, events, user instructions, agent outputs
Routing Core
Intent parsing, risk filters, policy checks, priority queues
Output
Trading agents, research agents, workflows, notifications
Key Properties
- Pluggable: works with existing infra
- Policy-aware: enforces rules and constraints
- Observable: every routing decision is logged
Use Cases
Multi-Agent Trading Stack
Route signals between research agents, on-chain executors, and risk filters to avoid conflicting or redundant trades.
Research & Alerting Mesh
Aggregate output from multiple LLM agents, scoring confidence and sending only the most relevant findings downstream.
Workflow Orchestration
Coordinate back-office automations, approvals, and notifications through a single routing layer instead of scattered scripts.
Prediction & Execution Bridge
Connect prediction markets, models, and execution agents so that outcomes can drive on-chain actions automatically.
Whitepaper & Token
The Frameworks Lab protocol and the $FRMX token are documented in our whitepaper, covering architecture, routing logic, and incentive design.
About $FRMX
- Used to secure routing policies.
- Aligns incentives between agents, builders, and infrastructure.
- Backs governance over new modules and integrations.