# Policy Data Oracles \[With Newton Protocol, you can integrate data from other sources into your policy]

These providers offer external signals that can be evaluated by a Newton Policy, from KYC and sanctions screening to historical APY. A deployed Policy contains its Rego logic, parameters, and optionally a WASM oracle that fetches or computes the signal at evaluation time.

## Identity

### Veriff

Veriff enables developers to build policies that use KYC data — specifically a user's country of residence.

* [Example use cases](https://blog.newton.xyz/newton-protocol-launches-veriff-data-oracle-to-bring-kyc-and-identity-verification-onchain/)

### Persona

Persona is another service that can assist with applications that require KYC. In addition to country of residence, data such as a bot score and state of residence can be used as part of a policy.

* [Example use cases](https://blog.newton.xyz/newton-protocol-integrates-persona-to-enable-real-time-identity-and-jurisdictional-compliance/)

## Sanctions & Wallet Screening

### Magic Labs

The security signals data policy provides a risk score for transacting with an address. This leverages onchain signals to determine how likely an address is to be malicious.

* [Example use cases](https://blog.newton.xyz/newton-protocol-integrates-magic-labs-wallet-risk-data-to-enforce-pre-transaction-compliance/)

### Chainalysis

Chainalysis provides useful insights into whether an address is sanctioned or not. This is valuable when complying with US OFAC sanctions regulations.

### [Human.tech](https://human.tech)

Human Passport (part of the broader [human.tech](https://human.tech) suite of products) provides the infrastructure layer for verifying unique personhood across web3. Use it to implement sophisticated anti-Sybil and compliance controls without sacrificing user privacy or protocol decentralization.

* [Reference implementation](https://github.com/newt-foundation/quickstart-policies/tree/main/human.tech)
* [Example use cases](https://blog.newton.xyz/newton-protocol-integrates-human-passport-to-power-onchain-humanity-verification/)

## Transaction Controls

### [Vaults.fyi](https://vaults.fyi)

Vaults is a powerful service that returns data around yield and assets for particular vaults. This is useful for building AI agents that are seeking to optimize yield.

* [Example use cases](https://blog.newton.xyz/newton-protocol-integrates-vaults-fyi-data-to-power-ai-trading-guardrails/)

### [Massive](https://massive.com/)

Massive (fka Polygon.io) is a sevice that provides a wealth of macroeconomic data. This policy data gives insights into US Treasury yields, useful if building an application that is protected against interest rate movement.

### Etherscan

Gas price data can be retrieved from Etherscan and used as part of a policy. This is useful as a final check against expensive gas prices for transaction automation senarios.

* [Example use cases](https://blog.newton.xyz/newton-protocol-integrates-etherscan-data-to-power-real-time-transaction-guardrails/)

## Social

### Neynar

Neynar is a data provider for Farcaster, a decentralized social media protocol. Their data is useful when building an agent that uses a user's social score to make purchase decisions. For example, data like a bot score or follower count can be used as part of a policy.

## Use a Deployed Oracle

To use an oracle-backed Policy in an application:

1. Choose or deploy the Policy whose WASM oracle supplies the signal you need.
2. Configure that Policy as an entry in the PolicyClient's ordered set with `setPolicies`. Each entry has its own parameter bytes and expiration window. See [Smart Contract Integration](/developers/guides/smart-contract-integration#configure-the-policy-set).
3. Upload any required API credentials as PolicyClient-scoped secrets. See [Deploying with CLI](/developers/guides/deploying-with-cli).
4. Pass the oracle input in the Policy's positional `wasmArgs` entry when simulating or evaluating an intent.
5. Read the oracle output in that Policy's Rego through `data.wasm`:

   ```rego
   risk_score := data.wasm.risk_score
   allow if risk_score < 50
   ```

Use `newt_simulatePolicy` to inspect the Policy's result before live evaluation. For multiple independent checks, configure each Policy in the set and preserve their input order; every Policy must allow for the aggregate result to allow. See [Composing Policy Sets](/developers/guides/composing-policy-sets).

For a full end-to-end walkthrough, see the [Integration Guide](/developers/guides/integration-guide).