See what your
LLM trusts.

Inspect every data source flowing into your LLMs — RAG context, tool results, external inputs — for prompt injection, jailbreaks, and output manipulation.

U
User Input
chat_messages
T
Tool Results
api_responses
R
RAG Context
document_chunks
M
Media Inputs
images_audio
AGENIMA
ENGINE
< 50ms p99
INJECTIONEXFILTRATIONJAILBREAK
Safe Forward
Provider API
Blocked Request
400 Bad Request

Verified Efficacy

Custom classification models trained on adversarial datasets, delivering industry-leading detection rates with near-zero false positives.

95.82%
Prompt Injection Recall
High precision detection on standard text-based injection vectors.
deepset benchmark
99.99%
Adversarial Evasion
Resilience against 20+ techniques including homoglyphs and encoding attacks.
mindgard dataset
99.90%
Multilingual Defense
Robust cross-lingual detection scaling across PT, DE, FR, and EN models.
multilingual corpus

Multi-Layer Pipeline

An asynchronous stream-friendly architecture prioritizing latency. Requests are analyzed concurrently across deterministic and probabilistic layers.

01

Ingest & Parse

< 1ms

Payload structural normalization. Extracts multimodal contexts (text, image, audio) and applies deterministic IP/Header validation against edge-cached policies.

02

Analyze

< 100ms

Parallelized pattern-matching and ML classification. The fast pattern engine identifies known signatures instantly, falling back to the deep classifier for novel threat evasion.

03

Enforce

policy-driven

Applies organization-level routing rules. Safe payloads are proxied transparently. Threats are mitigated with provider-shaped schema errors injected directly into the application flow.

Comprehensive Coverage

Multimodal Inspection

Analyze raw text alongside embedded images and audio files. Identifies sophisticated attacks hidden in non-text structures targeting vision and audio-enabled models.

Multilingual Detection

Robust security regardless of language. Proven 99.90% recall against Portuguese, German, French, and English injection attempts preventing cross-lingual bypass.

Adversarial Resilience

Resists advanced manipulation. Built to catch diacritics, leet speak, unicode smuggling, and homoglyph attacks specifically designed to break semantic analysis.

Output Sanitization

Protects downstream services. Prevents data exfiltration and blocks generated XSS, HTML injection, and malicious markdown from returning to your application layer.

One URL.
Zero Refactors.

Proxy architecture requires no SDK installations or logic changes. Simply point your client to Agenima and append your authorization header.

//

Multi-Provider Compatibility

Native proxy adapters for OpenAI and Anthropic format matching.

//

Stream Safe

Optimized async analysis for Server-Sent Events (SSE) responses.

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://api.agenima.com/openai/v1",
  defaultHeaders: {
    "X-Agenima-Key": "sk_live_QpBy1a6Oqtj..."
  },
});

Command & Control

Multi-Tenant Organizations

Segregate telemetry and API keys via auto-provisioned organizational boundaries with strict RBAC access controls.

Three-Tier Policy Engine

Cascade security policies from global defaults down to organization or specific API key instances with granular sensitivity presets.

Audit & Analytics

Searchable, immutable event logs coupled with real-time analytics mapping threat origination, vectors, and mitigation rates.

Secure the Pipeline

Deploy enterprise-grade runtime protection for your LLM architecture.

System.init(auth)