The Governed AI Workforce Platform

Console is where your organization employs AI agents: hire them, scope their permissions, supervise their work, and prove to an auditor exactly what they did. One deployable, under your control: private cloud today, on-premises and air-gapped on the roadmap.

Run AI Agents on Data You Can't Put in the Cloud

Sovereign AI agents inside your own boundary: on-prem, private cloud, or fully air-gapped. No public-cloud dependency. No compromises.

Your data stays yoursWorks offline

See the Console in Action

Watch agents take on real work, with their own identities, their own permissions, and a paper trail an auditor can check.

  • Agents with their own identity and permissions, not borrowed human logins
  • Every action lands in a tamper-evident, post-quantum-signed audit trail
  • Compliance evidence accumulates as the system runs, across 24 frameworks

Differentiators

Four Things Nobody Else Does Together

Not a feature list, but the specific architectural bets that separate Console from chatbot dashboards and permission-mirroring agent platforms.

Agents are employees, not borrowed logins

Most platforms mirror a human user’s permissions onto the agent asking. In Console, an agent is a first-class principal with its own privileges, duties, and audit record under one organization root, which is what recurring autonomous work, delegation between agents, and real accountability require.

Compliance as a product, not a property

Console doesn’t just pass its own audits. It works toward yours. 24 frameworks modeled as code, evidence collected as the system runs, and every verification run itself recorded in the audit trail an assessor can sample.

A post-quantum audit spine

Every audit record is HMAC-chained and signed with ML-DSA-65 (NIST FIPS 204) under versioned keys, then re-verified on a nightly schedule. Tampering, key rotation, and configuration gaps are distinguishable, by design.

Built for your boundary

One deployable that owns the runtime, API, admin surface, and data layer, with no per-feature SaaS sprawl. Private-cloud today; on-premises and air-gapped delivery are the roadmap, and the architecture is built to make them possible.

Proof, Not Promises

Don’t Take Our Word for It

Trust infrastructure should be checkable. Console’s audit guarantees are independently verifiable, by your team or your auditor.

Published verification keys

Every deployment exposes its audit-signing public keys (current and retired versions) so signatures can be verified without trusting the server that made them.

Nightly verification runs

The audit chain and every post-quantum signature are re-verified on a nightly schedule. Each run writes a dated evidence record: a sampleable population, which is what an assessor actually asks for.

Failures are findings

A failed verification isn’t hidden. It’s recorded as evidence, written into the signed audit spine, and raised as an alert. The system is built to tell on itself.

Architecture

Seven Layers. One Deployable.

A monolithic-but-modular architecture: a single deployable that owns the API, the agent runtime, the admin surface, and the data layer.

Multi-Tenant Data Foundation

PostgreSQL (Prisma, 120+ migrations), Neo4j knowledge graph, and Redis, with every query org-scoped by construction. Three databases, each doing what it’s built for.

Agent Execution Pipeline

A full state-machine runtime: plan → tool-execute → reflect → budget-check → stream. Cost accounting, human-approval gates, PII evaluation, and constitutional constraints baked in.

Context Assembly

7-provider context pipeline (RAG, graph-RAG, documents, customer data, compliance, financials, ontology) with security filtering, re-scoring, and token budget enforcement.

MCP Integration Layer

Model Context Protocol as the universal tool bus. 241+ tools across 14 integrations, discovered at runtime, not hardcoded. HubSpot, Autodesk, Google, and custom connectors.

Learning Loop

Human feedback capture and preference-pair extraction ship today; the adapter-training and promotion pipeline is in active development. Built so the system can improve from operation.

Compliance Engine

343 controls across 24 regulatory frameworks (HIPAA, CMMC, SOC 2, NIST 800-171, GDPR, ISO 27001) modeled as code: automated checks and evidence for a growing subset, structured attestation workflows for the rest. POAM tracking and SPRS scoring included.

Trust & Identity

Privilege-based access control where agents and humans are the same kind of principal, a cryptographically signed audit spine, and device attestation rolling out through the native apps. DID-based agent identity is in development.

Shipped and Roadmap: Clearly Labeled

Every vendor says everything ships. Here’s our actual line between running code and active development.

Shipping today

Multi-Agent Orchestration
Graph + Vector RAG
PBAC: 137 Privileges
Agents as First-Class Principals
HMAC-Chained Audit Log
ML-DSA-65 Signed Audit Trail
Nightly Chain Verification
Published Verification Keys
Human Approval Gates
Scheduled & Recurring Agent Work
24-Framework Compliance Tracking
MCP Integrations: 240+ Tools

In active development

Enterprise SSO
On-Premises Turnkey Install
Air-Gap & Disconnected Ops
SSI / DID Agent Identity
RLHF Adapter Training & Serving
FedRAMP Pathway
“Console is built for the assumption that AI agents become autonomous principals in enterprise workflows, not assistants. Every architectural decision is load-bearing for that thesis.”

Enterprise-Grade Security

Built for organizations with the strictest compliance requirements

SOC 2 Type 1

Preparation underway · 2026

CMMC / NIST 800-171

110 controls mapped · SSP maintained

HIPAA

Control framework live · pathway in progress

Post-Quantum Crypto

ML-DSA signed audit trail · FIPS 204

Your AI. Your Hardware. Your Rules.

See how Console runs a governed AI workforce on infrastructure you control, from a single team to a regulated enterprise.