automated decision support
for onchain risk

leverage artificial intelligence to manage risk and build genuinely permissionless financial networks on the blockchain

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frwd research

risk management and open financial networks are not mutually exclusive. but to work together, they need a new paradigm.

it starts with understanding the nature of permission.

whitepaper coming soon

Manage Regulatory Risk for Real World Assets

With Auditable Reasoning

Auditable reasoning graph showing how a transaction is classified as Sophisticated (p = 0.875) by composing primitive predicates over a sender's prior intent.

Onchain Capital Formation Requires Composability

Composability Requires Common Primitives

Simplified knowledge graph: primitives composing into Wash Trading Risk Four onchain primitives (Self-Trade, Same Cluster, Round-Trip, Zero P and L) compose upward into two intermediate predicates (Coordinated Counterparties and Wash Cycle), which together yield a Wash Trading Risk classification with probability 0.92. Wash Trading Risk p = 0.92 Coordinated Counterparties Wash Cycle Self-Trade Same Cluster Round-Trip Zero P&L

Real Time. Not Reactive.
Dynamic. Not Static.

Blockchain-based risk infrastructure requires real time controls that can adapt.

Vintage engineering plate of mechanical clockwork — gears, escapements, and adjustable timing wheels — a metaphor for adaptive real-time risk controls.

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about frwd labs

frwd labs builds behavior-first onchain intelligence: real-time transaction and interaction analysis of how wallets move, cluster, and coordinate across blockchain ecosystems.

designed for compliance teams, protocol risk analysts, and security engineers who need actionable intelligence.