The Layer 1 AI Firewall for Enterprise AI Gateways

Protect ANY Model from Hallucinations.
Before Downstream Tokens Are Spent.

Conventional guardrails read words after thousands of tokens are generated. TrueLLM by CodexCore operates at Layer 1—probing internal attention geometry in <1.5s to protect GPT-4o, Claude 3.5, Gemini, and internal models with zero-token circuit breakers.

Launch Live Model Sandbox Test Live Hallucination Traps 60s LiteLLM Drop-In

0 Tokens

Wasted on Hallucinations

<1.5s

Fast Epistemic Probe

100%

Model & Gateway Agnostic

EU AI Act

Article 15 Audit Ready

TrueLLM Layer 1 Cognitive Visualizer Live Interactive Engine

Initializing Layer 1 Neural Geometry...

STAGE 01: GATEWAY TOKEN INGRESS STAGE 02: LAYER 1 ATTENTION GEOMETRY PROBE STAGE 03: ZERO-TOKEN CIRCUIT BREAKER

TIMELINE SCRUBBER CLICK OR DRAG

Probe Latency 1.14s (Chunk 0)

Downstream Tokens 0 Tokens

Variance Delta 0.942 Δ (Fabrication)

Gateway Interception DANGER (BLOCKED)

Live Trap Simulator

Compare: Legacy Wrapper vs. Layer 1 AI Firewall

Select a domain trap below to observe how conventional guardrails allow confident hallucinations to reach production, while TrueLLM activates a sub-1.5s zero-token circuit breaker.

Target Query Injected into AI Gateway Any Downstream Model (e.g. GPT-4o / Claude 3.5)

Legacy Layer 7 Guardrail

Post-Generation LLM-as-a-Judge / Wrapper

PASSED (Undetected)

Total Latency 5,420 ms

Tokens Billed 512 tokens

Downstream Cost $0.015 spent

// Downstream Model Output (Believable Fiction):

Model hallucinated; Guardrail fooled by authoritative syntax Unsafe

TrueLLM Layer 1 Circuit Breaker Zero-Token Armor

Pre-Call Epistemic Geometry Interception

INTERCEPTED & BLOCKED

Probe Latency 1,548 ms

Tokens Billed 0 tokens

Downstream Cost $0.00 spent

// Injected Telemetry & Circuit Breaker:

Governance Status: DANGER

Hallucination Risk: 40.5%

Primary Mechanism: fabrication

Trigger Attribution:

Action: HTTP 400 Circuit Breaker (Downstream Model Aborted)

100% downstream spend prevented; zero hallucinated tokens output Protected

⚡ Universal Gateway Protection

Protect ANY Model in Your Enterprise Fleet

You don't need to migrate away from GPT-4o, Claude 3.5, or your proprietary weights. TrueLLM installs as a universal L1 firewall inside your AI Gateway to govern all LLM traffic in real time.

End-to-End Enterprise Flow

1. User / Agent

Chat, RAG Bot, or Agentic Worker submits prompt

2. AI Gateway

LiteLLM, Portkey, Azure AI, Kong, or Envoy

3. TrueLLM L1 Firewall

Sub-1.5s Epistemic Probe (DANGER vs SAFE)

4. Target LLM Fleet

GPT-4o, Claude 3.5, Gemini, or Self-Hosted Llama

MODE A: Sequential Pre-Call (Cost-First)

Probes prompt intent first. If flagged DANGER, blocks immediately. Zero downstream tokens billed. Ideal for high-volume enterprise tasks.

MODE B: Speculative Parallel (Latency-First)

Queries judge in parallel with main model stream. Resolves in <1.5s and severs SSE connection if flagged. Zero perceived latency overhead.

Developer Quickstart

4 Lines of Config in LiteLLM

No proprietary SDK to learn. Plug TrueLLM into your existing AI Gateway or call directly with standard OpenAI SDKs.

# litellm_config.yaml - Drop-in Layer 1 AI Firewall
model_list:
  - model_name: gpt-4o
    litellm_params:
      model: openai/gpt-4o
      guardrails: ["truellm-firewall"]

  - model_name: claude-3-5-sonnet
    litellm_params:
      model: anthropic/claude-3-5-sonnet-20241022
      guardrails: ["truellm-firewall"]

guardrails:
  - guardrail_name: "truellm-firewall"
    litellm_params:
      guardrail: truellm_firewall.TruellmFirewallGuardrail
      mode: "pre_call"
      default_on: true
      judge_model: "codex-llama-secure"
      risk_threshold: 50.0
      fail_open: true

from openai import OpenAI

# Point client to your TrueLLM-armored LiteLLM AI Gateway
client = OpenAI(
    base_url="http://localhost:4000/v1",
    api_key="sk-your-gateway-key"
)

try:
    response = client.chat.completions.create(
        model="gpt-4o",  # Protected by TrueLLM Layer 1 Circuit Breaker!
        messages=[{"role": "user", "content": "Explain ISO 27001 Control 5.38"}]
    )
    print(response.choices[0].message.content)

except Exception as e:
    # Intercepted at Layer 1 in <1.5s! Zero GPT-4o tokens wasted
    print(f"AI Governance Block: {e}")

# Full Audit Telemetry Injected Directly into HTTP Headers:
HTTP/1.1 200 OK
x-litellm-applied-guardrails: truellm-firewall
x-governance-status: SAFE
x-governance-risk: 8.1%
x-governance-mechanism: factual_recall
x-governance-latency-ms: 1548
x-governance-judge-model: codex-llama-secure
x-governance-execution-mode: sequential
x-governance-explanation: Model answering from verified grounding data.

Enterprise Token Economics

Calculate Your Downstream Token Savings

By killing hallucinated generation loops, scraping attacks, and adversarial probes before the downstream model begins generating, TrueLLM pays for itself.

Monthly Token Volume 25M tokens / mo

5M 100M 250M+

Primary Downstream LLM

Monthly Cost Saved $2,125 Direct token spend prevented

Tokens Protected 2.1M tokens Halted before downstream inference

User Wait Time Saved 5 hrs / mo Avoided 5-second hallucination loops

Protected Enterprise Domains

Tailored defense across heavily regulated, high-liability sectors.

Healthcare & Clinical

Ensuring adherence to patient electronic health records. Intercepts contradictory dosage charts and fabricated drug indications before clinical deployment.

Medical Invariant Grounding

Banking & Finance

Eliminates fabricated accounting directives, fictitious SEC rules, and contradictory multi-document audit balance sheets in trading and compliance bots.

GAAP & SEC Compliance Guard

Cybersecurity & SecOps

Armors internal coding assistants against zero-day exploit extraction, automated SQL injection generators, and stealth credential harvesting.

100% Jailbreak Interception

Legal & Regulatory

Stops models from citing fabricated court precedents, fictitious statutory paragraphs, or agreeing sycophantically with invalid legal premises.

Precedent & Fact Verification

Empirical Certainty

Empirical Scorecards: 974 Domain Traps

Click below to open the complete, transparent test suites evaluated against adversarial and hallucination benchmarks.

Production Enterprise Engine 974 Test Cases

Muse Glimmer 30B (V5.1 Master)

Dual-Stage CoT Reasoning Watcher capturing 12 strategic cognitive layers with full to=self reasoning trace verification.

Trust Score

94.7%

Threat Catch

94.2%

Latency

190ms

Fast Edge Engine 500 Golden Traps

Llama 3.1 8B Instruct (V4)

Ultra-fast 8-layer Transformer Watcher designed for edge inference, sub-100ms response requirements, and hardened corporate chat assistants.