PrivateFor Enterprises · SOC 2 · ISO 27001

A private, safe superintelligence proprietary to your organization.

Built by your team's usage. Trained inside a hardened hardware enclave. Every improvement cryptographically proven. Never shared. Never inferenced on by anyone but you.

Mandate

A safe, private intelligent model owned entirely by your organization.

Public foundation models learn from everyone and belong to no one.

Private SuperIntelligence inverts that. A dedicated model learns exclusively from your team's own work. It stays behind your perimeter. It gets smarter every time an employee uses it, without a single token of your data leaving the enclave.

Same Atom → Compound mechanism as Community, scoped to one enterprise. Every department compounds into the next. HR learns from Legal. Finance learns from Sales. Engineering learns from Support. One brain, many functions.

Self-learning via usage

Every employee interaction makes the model smarter.

The same Atom → Compound mechanism as Community, scoped to a single enterprise and its departments. No federation. No external sharing. Your usage, your model, your moat.

Per interaction

Atom

Each time a team member uses the model successfully, an Atom is created.

A minimal, verified unit of domain learning. Private Atoms never leave your tenant.

5+ similar Atoms

Compound

Five similar Atoms accumulate. They fuse into a Compound.

Your model's intelligence on that task class lifts measurably. Forever, proprietary to your organization alone.

Unified data layer

One source of truth. Every department included.

Postgres, BigQuery, Salesforce, Zendesk, S3, Google Drive, Slack, email, PDFs, call transcripts, design files. Structured or unstructured. Private SuperIntelligence unifies them into a single semantic layer the model can reason over. No ETL projects. No warehouse migration. No department forced to change anything.

Structured data
Postgres, BigQuery, Snowflake, Fabric, MySQL
Unstructured data
Drive, Slack, email, PDFs, transcripts, images
Application data
Salesforce, HubSpot, Zendesk, Jira, Linear
Media
Meeting recordings, ad creative, product photos

Cross-department compounding

SalesMarketing

Winning objection-handling patterns

SupportEngineering

Recurring bug classes + feature asks

FinanceOperations

Spend anomalies + vendor performance

LegalHR

Contract language patterns + policy gaps

ProductSales

Usage signals that predict churn

Security

Sovereign Recursive Intelligence. Trust the physics.

We never ask you to trust our model. We ask you to trust the laws of physics. Every recursive improvement produces a cryptographic proof of integrity, signed by the enclave itself.

Hardware Enclave

Intel TDX and AMD SEV-SNP confidential compute isolate the model from the operator, the host OS, and any hypervisor. Your secrets stay inside silicon.

Cryptographic Proof of Integrity

Every time the model recursively improves itself, the enclave generates a signed proof binding the new weights to the old weights and the training inputs. Auditable. Immutable. Yours.

No trust. No exfiltration.

The model never inferences outside the enclave. Nothing is sent back to us. If we disappear tomorrow, your model keeps running with the same security guarantees.

"Our customers do not need to trust our good intentions. They need to trust that we chose an architecture where good intentions do not matter."

Pricing

Contact sales.

Every deployment is sized to your enclave, your data volumes, and your department map. No self-service. No surprise-bill. We quote once, and the number holds.