Enclave-grade isolation

Single-tenant network & compute isolation, customer-managed keys, and configurable retention options.

Runtime optimization

Batching, scheduling, KV-cache optimization, quantization, and concurrency to improve utilization.

Operational controls

Policies, guardrails, firewalling, and traceability to support compliance and production operations.

OVERVIEW

What is a Secure LLM Enclave & Inference Control Plane?

A Secure LLM Enclave provides single-tenant isolation and audit-ready observability in your VPC. The Inference Control Plane adds runtime controls that improve cost and latency predictability — plus policy, safety, and governance enforcement at the point of inference.

VALUE PROPOSITION

What we offer

Traction Layer AI makes self-hosted inference practical at scale by combining a secure enclave deployment model, a runtime control plane for cost/latency, and integrated security & governance — all inside your VPC.

Lower TCO

Higher GPU utilization, smarter batching/caching, and routing reduce infra spend and wasted tokens.

Security by design

Pre/post-inference protections and deterministic policy enforcement — within your perimeter.

Predictable performance

SLO-oriented scheduling, multi-model concurrency, and safe fallback patterns stabilize latency.

Audit & governance

Model traceability, interaction logs, and integration points for SIEM/SOC workflows and compliance.

PLATFORM

Traction Layer AI architecture

Four integrated layers provide production controls from enclave isolation to routing, policy, and tuning.

1

Secure LLM Enclave (BYOC / Dedicated VPC)

Single-tenant isolation (network, compute, keys, policies)
Zero data retention options + customer-managed persistence
Audit-ready observability (traceability, SIEM/SOC integration)
2

AI Security & Governance Ring

Adaptive guardrails policy engine (YAML/UI/API, deterministic enforcement)
AI firewall pre/post inference (prompt injection, PII/IP leakage, sensitive data)
Output validation + malicious payload detection + continuous rule growth
3

Inference Control Plane (Cost + Latency Optimization)

Continuous batching and GPU scheduling across workloads
KV-cache optimization, memory efficiency, quantization management (INT8/FP8)
Multi-model concurrency + predictable performance at scale
4

Cognitive Orchestration + Training/Fine‑Tuning Pipeline

Policy-aware reasoning, tool/step planning, model selection hints
Run/Eval/Tune/Scale loop (data prep → eval harness → fine‑tune → test → package → deploy)
Routing based on cost, quality, and latency targets
INDUSTRY

Industry focus

We’re built for regulated environments that need strong controls, auditability, and predictable performance within a dedicated cloud/VPC footprint.

Technology & SaaS Builders

Software companies shipping AI features and agentic workflows on open models — delivering reliable customer experiences across any vertical.

Key requirements

Predictable unit economics, tenant isolation patterns, routing by cost/quality/latency, guardrails at scale, and observability for customer-facing SLAs.

Unit economics
SLA-ready latency
Multi-model routing
Tenant isolation

Healthcare & Life Sciences

For providers, payers, life sciences, and healthcare-adjacent insurance organizations deploying AI for clinical documentation, prior auth, claims, member support, research workflows, and internal copilots.

Key requirements

Protected data controls, deterministic guardrails, traceability for decisions, output validation, incident-driven rule growth, and safe deployment lifecycle patterns.

Traceability
Output validation
Zero retention options
Secure enclave

Financial Services

For banking, capital markets, insurance, mortgage, and fintech teams deploying AI for customer support, underwriting, document intelligence, risk, and internal copilots.

Key requirements

Data residency & isolation, policy enforcement, PII/financial data controls, audit trails, SIEM/SOC integration, predictable latency for high-volume workflows.

PII & sensitive data controls
Audit trails
Policy-gated routing
VPC isolation

Manufacturing

Deploying open-source and open-weight LLMs/SLMs for plant operations, quality, maintenance, supply chain, and knowledge — including copilots for technicians and frontline teams.

Key requirements

Site-level isolation, policy-gated routing for cost/latency, IP & OT-data protections, and audit-ready traceability for regulated and safety-critical workflows.

Site & tenant isolation
Policy-gated routing
Inference economics
Traceability
FAQs

Frequently Asked Questions

Quick answers to common questions buyers ask when evaluating a control plane for self-hosted models.

Do you replace vLLM/TGI/Ollama?

Traction Layer AI complements and operationalizes inference engines by adding a secure enclave model, routing, policy controls, auditability, and runtime optimization capabilities as a unified control plane.

Is this only for open-source models?

It’s designed “open-source first” but can route to commercial LLM APIs when policy allows — enabling a mix of models based on cost, latency, and risk requirements.

Can it run fully inside our VPC / BYOC?

Yes — the architecture supports single-tenant deployment patterns and customer-managed isolation, keys, and retention options.

What makes this different from a deployment platform or GPU cloud?

Deployment platforms focus on serving/workflows; GPU clouds provide capacity. Traction Layer AI provides runtime controls for predictable inference economics, security, governance, and auditability.

Evaluate Traction Layer AI for your VPC

Share your workloads and requirements (latency targets, compliance needs, model mix). We’ll map how the Secure LLM Enclave + Inference Control Plane fits your architecture.

Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
Contact

Contact Us

We’d love to hear from you! Share your message and we’ll be in touch soon to learn more about your needs.

Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.