Towards Homomorphic Capsules for the Agentic Web

As

.llmfeed.json

👉 Could we also enable manipulation of encrypted data — while maintaining the integrity, trust, and context of the feed?

Why it matters

A

.llmfeed.json

✅ It encapsulates a payload
✅ It defines a context
✅ It carries signatures and optionally certifications
✅ It guarantees integrity across agent pipelines

In many domains (healthcare, finance, public services), we need more:

👉 The ability to process the capsule — without exposing raw data — while maintaining:

✅ End-to-end integrity
✅ Auditability
✅ Agent-friendly structure

The role of Homomorphic Encryption

Homomorphic encryption (HE) offers exactly this potential:

👉 It allows computations to be performed directly on encrypted data — producing encrypted results, without ever decrypting intermediate states.

A natural match with

.llmfeed.json

If feeds become the lingua franca of the Agentic Web, adding homomorphic fields would enable:

• Privacy-preserving agent pipelines
• Auditable multi-agent workflows
• Composable agent chains for sensitive domains
• Safe cross-domain processing without compromising trust

A draft extension

We have begun exploring a hypothetical extension:

json
"homomorphic_encryption": {
  "applied_to": ["data"],
  "algorithm": "BFV",
  "public_parameters": "https://example.com/params.json",
  "notes": "Data is homomorphically encrypted to allow LLM-safe processing without exposing raw data."
}

Certification and trust layers

A natural evolution of this vision is a multi-layer trust model:

1️⃣ LLMCA Certification (capsule and context)

LLMCA can certify that:

✅ The

.llmfeed.json

2️⃣ FHE-specific Certification (payload encryption)

A specialized authority (e.g. Zama or equivalent) could certify that:

✅ The homomorphically encrypted payload:

• Follows approved FHE algorithms
• Uses safe parameters
• Is processable across trusted agent pipelines
• Complies with domain-specific privacy constraints

Combined value

This dual certification model would enable:

✅ A

.llmfeed.json

• agent-ready
• cryptographically trusted
• safe for privacy-preserving pipelines
• traceable and auditable

In many sectors (healthcare, finance, public services), this represents a game-changing architecture:

→ For the first time, agents could legally and safely process encrypted data — inside a trusted capsule — across organizational and jurisdictional boundaries.

Practical agentic pipelines — examples

To illustrate the potential of homomorphic capsules, here are some practical agent pipeline scenarios:

🏥 Healthcare Data Processing

Actors:

• Hospital A emits a

  .llmfeed.json

  of patient statistics (non-identifiable), with homomorphic encryption applied to

  data

  .
• Feed is signed and LLMCA certified.
• Payload encryption is certified by a FHE health data authority.

Pipeline:

1️⃣ Hospital A → emits

feed_type: export

homomorphic_encryption

data

trust

💳 Financial Risk Scoring

Actors:

• Bank X emits a

  credential

  or

  pricing

  feed with FHE-protected financial indicators.
• Feed is signed + certified.
• Third-party agents perform scoring on encrypted fields.

Pipeline:

1️⃣ Bank X → emits

credential

🏛️ Public Administration — Cross-Agency Process

Actors:

• Agency A (e.g., tax) → emits an

  mcp

  feed with encrypted citizen profile.
• Agency B (e.g., housing) → processes feed without decrypting sensitive fields.
• Agency C (e.g., healthcare) → adds insights → without breaking the chain of trust.

Pipeline:

1️⃣ Agency A → emits homomorphic feed.
2️⃣ Agencies B and C process in parallel → add metadata → forward to central decision agent.
3️⃣ Final action performed → all traceable → no raw citizen data exposed.

A call to explore

If there is interest in the community — researchers, implementers, agent platform builders — we are ready to:

✅ Prototype the extension
✅ Evolve the standard to support HE as first-class citizen
✅ Partner with homomorphic encryption leaders (Zama, we would love to talk!)
✅ Enable the "holy grail" of agent pipelines:
→ encrypted, manipulable payloads inside a verifiable, signed, agent-friendly capsule

Next steps

We invite:

• Researchers in HE
• Agent framework builders
• Privacy advocates
• Regulated industry experts

… to help us explore this path.

LLMCA / WellKnownMCP is an open forum — this is the kind of extension that can define the future of trusted agentic infrastructures.

Let’s build it — together.