---
title: "Use cases"
description: "Explore use cases where GenLayer can resolve shared outcomes from natural language, public evidence, and subjective criteria."
source: https://docs.genlayer.com/understand-genlayer-protocol/typical-use-cases
last_updated: 2026-08-19
---

# Use cases

GenLayer is useful when an application needs a shared, enforceable outcome but the decision cannot be reduced to deterministic onchain data. The strongest use cases have explicit criteria, accessible evidence, meaningful consequences, and participants who benefit from a neutral appeal process.

Use the [builder fit checklist](/developers/intelligent-contracts/when-to-use-genlayer) before choosing GenLayer over a conventional smart contract or backend.

## Performance and milestone decisions

An Intelligent Contract can assess whether work satisfies a written specification and release an onchain outcome.

Examples include:

- bounty payouts based on deliverable quality;
- grant tranches based on milestone evidence;
- freelance escrow based on acceptance criteria;
- service-level agreement claims; and
- retroactive funding based on documented impact.

The contract should identify the authoritative submission, rubric, deadline, and behavior when evidence is unavailable.

## Markets and claims

Markets and coverage products often depend on a public event whose resolution still requires interpretation.

Examples include:

- prediction markets with a natural-language resolution rule;
- flight, weather, or shipping claims based on several public sources;
- chargeback evidence from counterparties and carriers; and
- structured evaluation of insurance evidence.

For high-value or regulated uses, GenLayer can implement the technical decision process, but it does not replace the legal agreements, licensing, jurisdiction, or human escalation a product may require.

## Agent-to-agent commitments

Autonomous agents can pay, exchange tasks, and report results, but a counterparty still needs a way to challenge incomplete or low-quality work. GenLayer can evaluate a task specification and its evidence, then settle escrow or update reputation.

Examples include:

- whether an agent-delivered job meets its requested scope;
- whether an API or agent met a service-level commitment;
- which participant caused a multi-agent workflow to fail; and
- whether a disputed reputation report is supported by evidence.

## Policy and rule evaluation

Natural-language policies can guide an outcome while validators independently check the relevant evidence.

Examples include:

- whether a DAO proposal complies with its charter;
- whether a submission meets community guidelines;
- whether a market satisfies listing rules; and
- whether a process followed a published policy.

Avoid treating an LLM response as legal or compliance advice. Use authoritative data, encode objective checks where possible, and define who can update the governing policy.

## Content and information assessment

GenLayer can combine web retrieval, structured extraction, and qualitative validation for tasks such as:

- plagiarism or attribution review;
- evidence-backed content classification;
- code or document review against a rubric; and
- summarizing public information into a structured decision.

Store only the output the application needs. Large source documents and validator reasoning can be expensive, privacy-sensitive, and difficult to reproduce.

## A common contract pattern

Across these examples, a robust Intelligent Contract usually:

1. fixes the question, eligible outcomes, evidence sources, and deadline;
2. retrieves or receives the evidence in a non-deterministic block;
3. returns a small, structured proposed result;
4. asks validators to check the result against independent evidence and explicit criteria; and
5. applies the accepted result through deterministic state changes or messages.

[Build your first Intelligent Contract](/developers/intelligent-contracts/first-contract).