> For the complete documentation index, see [llms.txt](https://bluwhale.gitbook.io/bluwhaleai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://bluwhale.gitbook.io/bluwhaleai/architecture/overview.md).
# Overview
The Bluwhale Protocol fits seamlessly between the application layer and protocols plus L1/L2 chains, passing on crucial aggregated user insights to dApps and individuals without them needing to manually do the analysis or write the technical queries.
The personalization layer can further be broken down into core 3 modules
1. Data Verification Module
This layer consists of verifiers from the community, social interactions, and circles, tasked with validating the attestation to confirm the layers' secure and accurate operations, including the data contributed and identities established in Bluwhale’s AI network.
2. Identity Embedding Module
This layer authenticates users via both traditional (web2) social accounts and blockchain (web3) like social reference mechanisms, aggregated under the embedding. It integrates identities and data through knowledge links, weights, rankings, and other identity contextualization models.
3. Privacy Inference Module
Established on a Zero-Knowledge foundation, it interprets and shadows data consumers reveal and release, allocating rewards according to the demand from enterprises or individuals as well as the amount of processing and queries required to extract the full understanding and insights around the wallet/user.
Each of the modules are critical for the entire personalization layer to become trustless, decentralized and secure. The Data Verification Module ensures that contributed internal, external, on-chain/off-chain data seamlessly integrates with each other by leveraging a reference verification approach through nodes. The Identity Embedding Module contextualizes user behavior and continuously optimizes incoming references and data which make the profile as wholistic as possible. Then it passes the embeddings with its descriptive surrounding data to a zk-layer that only allows enterprises to access if the individual wallet holder gives permission to its data in exchange for financial rewards.
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