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Platform

Private AI Platform for Sensitive Workloads

Build and operate on-prem or hybrid AI systems with strict data boundaries, auditable context access, and operational observability designed for production teams.

Portfolio lanes

How the portfolio fits together

FlexInfer focuses on operational readiness in private environments: repeatable deployment controls, healthcare-aligned integration tooling, and a roadmap for enterprise context governance.

Runtime and inference control plane

FlexInfer

Kubernetes-native routing, deployment controls, and operational workflows for predictable on-prem or hybrid inference.

Deployment boundary
Model runtime placement, rollout safety, and capacity controls inside your cluster boundary.
Integration boundary
Inference APIs and platform operations remain inside your network and observability stack.
Context and orchestration control plane

Loom Core

Registry-driven MCP config generation, daemon routing, and enterprise context controls roadmap (gateway, RBAC, executor).

Deployment boundary
Centralizes MCP server lifecycle and policy boundaries for internal tools and agent access.
Integration boundary
Defines how agents reach internal systems with auditable routing and least-privilege intent.
Sensitive-data integration plane

fi-fhir

Healthcare-focused ingestion and transformation workflows (HL7v2 to FHIR) with profile-driven, testable data handling.

Deployment boundary
Data transformation pipeline runs in your controlled environment and deployment topology.
Integration boundary
Profile-driven mapping and validation isolate source variability while preserving operational traceability.
Operational surfaces

Operator mission-control surfaces

Loom Core governs context and policy boundaries. MentatLab adds the operator-facing orchestration UX for DAG design and run visibility.

Agent and DAG orchestration UI

MentatLab

Mission Control interface for building, monitoring, and executing DAG-based agent workflows in private environments.

Loom Core governs context routing and policy boundaries; MentatLab provides the operator UX for DAG design and run visibility.

Deployment boundary
UI, gateway, and orchestrator services run inside your Kubernetes footprint alongside internal agent workloads.
Integration boundary
Connects orchestration workflows to internal MCP-governed tools and runtime services without moving data to shared SaaS control planes.
Enterprise capability map

Current foundations and in-progress controls

Gateway, RBAC, and Kubernetes executor capabilities are currently in progress. Operational foundations are available today.

MCP Gateway
In progress
Centralized MCP routing layer for enterprise tool aggregation and policy enforcement.
Creates a single context ingress with controlled routing, auditing, and operational visibility.
Explore →
Role-based Access Control (RBAC)
In progress
Role-aware permissions for MCP tool access across teams and environments.
Supports least-privilege context access and clearer security boundaries for sensitive workloads.
Explore →
Dev-box Container Executor on K8s
In progress
Containerized execution path for development and automation workloads in Kubernetes.
Moves execution into controlled cluster infrastructure with consistent isolation and audit trails.
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Operational Foundations
Available
Production patterns already available: observability, workflow docs, and deployment controls.
Provides the baseline operating model while enterprise controls are being rolled out.
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Industry proof

Healthcare-aligned implementation stories

A healthcare-first proof path demonstrates how this portfolio handles sensitive data transformations and operational reliability in private environments.

Healthcare

fi-fhir healthcare integration workflows

Profile-driven parsing and transformation for HL7v2 and FHIR in production-oriented workflows.

Healthcare

Operationalizing healthcare API integrations

Reliability patterns for long-lived, partner-facing integration surfaces under operational pressure.

Next step

Move from positioning to execution

Start with a readiness audit to baseline risk, cost, and deployment constraints. Then scope architecture work for your environment.