> For the complete documentation index, see [llms.txt](https://docs.nerve-protocol.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.nerve-protocol.com/product/features.md). # Feature Grid Nerve Protocol is a privacy-native AI operating layer. Every capability listed here executes inside hardware-isolated enclaves. The host never sees plaintext data, prompts, or results. ## Encrypted Collaboration (Real-Time Workspaces) Shared mission spaces where all participants operate inside the same TEE boundary. * **Encrypted Session Workspace:** Multiple operators and AI agents share a live enclave context. Data synchronized between participants is encrypted in transit and at rest; the host only ever observes ciphertext. * **Presence Obfuscation:** Operator presence indicators are replaced with pseudonymous tokens until mutually disclosed via an authenticated handshake. No external observer can determine who is in a session or when they joined. * **Branching Mission Threads:** Missions can be forked and merged without creating gaps in the attestation trail. Each branch inherits the parent's policy capsule and emits its own compliance receipts. ## Circuit-Level Integrations TEE-native connectors that bridge external systems without breaking the cryptographic perimeter. * **Universal Connectors:** Connect SaaS APIs (Uber, Amazon, Slack, Notion, Google Workspace), on-chain data feeds, and air-gapped stores through [Secure Data Connectors](/overview/data-integrators.md). OAuth tokens are sealed to the enclave — exfiltration attempts trigger automatic revocation. * **Purpose-Bound Policy Mesh:** Every integration carries a policy capsule defining allowed data fields, intent, retention window, and expiration. Any agent action that violates the capsule triggers an automatic disconnect and is logged to the Coordination Ledger. * **Post-Quantum Relay Channels:** Intermediate data hops between enclaves over encrypted channels resistant to both current and future cryptographic attacks. ## Signal Extraction Engine Turns fragmented, multi-source data into a unified, queryable knowledge graph — without the raw data ever leaving the enclave. * **Multi-Source Normalization:** Reconciles inputs from SaaS APIs, blockchains, hardware sensors, and document stores into a consistent schema inside the TEE. * **Contextual Knowledge Graph:** Builds and updates a personal semantic index in real time, optimized for on-device LLM queries. The graph lives encrypted under operator-held keys and is never shared with the inference backend. * **Encrypted Analytics Dashboard:** Aggregated signals are rendered exclusively within the operator's active session. Closing the session wipes the rendered view; only the encrypted source data persists. ## Autonomous Executors Agents that run end-to-end inside TEEs, enforcing policy at the hardware level rather than the application layer. * **TEE-Bound Agent Runtime:** Executors receive only the context slice their policy capsule allows. They run on attested hardware; each task step requires a fresh attestation check before proceeding. * **Zero-Knowledge Policy Enforcement:** Compliance rules are compiled into zk circuits. Enforcement proofs demonstrate that the agent followed its constraints without revealing the rules themselves or the data they operated on. * **Self-Healing Workflow Engine:** Failed steps are automatically retried within policy bounds. Each retry emits its own receipt so the full execution history is auditable without replaying the original data. ## Intelligence Privacy Layer Model inference and personalization that runs sealed, with no model provider able to observe queries or outputs. * **Encrypted Inference Streams:** Results from Soma and Myelin are encrypted before they leave the TEE. Only the session's private key can decrypt the response — not the inference node operator. * **Isolated Agent Personas:** Operators can run multiple AI configurations (e.g. one for financial analysis, one for operational workflows) within separate enclave contexts, each with its own policy capsule and memory scope. * **Metadata Intent Shielding:** Query patterns, access frequencies, and API call signatures are obfuscated so external services cannot infer what the operator asked, what data was accessed, or why. ## Operator Console Experience The Nerve Console exposes the full protocol stack through a single encrypted interface. * **Command Palette (`CTRL + REDPILL`):** Spawn agents, route intents, and inspect live attestation states from a keyboard-driven overlay — no plaintext state written outside the enclave. * **Pre-Built Mission Playbooks:** Launch complex workflows (investor briefings, incident response, compliance reports) from signed, reproducible templates that are hashed and committed before execution. * **Cryptographic Presence Masks:** Session participants appear as pseudonymous operator IDs. The outside network sees only encrypted overlay traffic with no timing correlation to individual actions. ## Compliance and Audit On-demand proof of what happened, without exposing what the data contained. * **Zero-Knowledge Audit Receipts:** Each mission stage produces a zk proof asserting policy compliance. Receipts are exportable to regulators, partners, or auditors and verifiable without access to the underlying data. * **Immutable Attestation Ledger:** A tamper-evident log of enclave proofs, agent manifests, and policy states. Can be replayed to reconstruct mission integrity without reconstructing mission content. * **Programmable Policy Definitions:** Compliance requirements are expressed as code in policy capsules — versioned, auditable, and enforceable at the hardware level rather than relying on application-layer controls. Curious how these components compose end-to-end? Read [How It Works](/product/how-it-works.md) or review the [Architecture Overview](/architecture/nerve-protocol-infrastructure-overview.md). --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://docs.nerve-protocol.com/product/features.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. 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