The leading AI Control platform

Real-time
Control over all
your AI apps

Use Aporia to stay up-to-date with the most advanced
methods to mitigate hallucinations, prompt injection attacks,
inappropriate responses and other AI risks so you can
focus on shipping the best AI apps.

Trusted by enterprises worldwide

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Why Aporia?

No Control, No Go

AI can feel like magic, when kept under control. Without proper guardrails, both customer-facing AI apps and internal apps can present significant risks.

Aporia Guardrails
Mitigate

Real-Time

Hallucination Mitigation

Improve user trust by mitigating incorrect facts, nonsensical responses, and semantically incorrect LLM-generated SQL queries.

Start mitigating
Enforce

Block Prompt Injection Attempts

Secure your AI models against prompt leakage, jailbreak attempts and other types of prompt injection attacks.

Block Injections
Govern

Custom AI Policies
Tailored To Your Needs

Tailor ethical AI guidelines, ensuring responsible interactions and safeguarding your brand's integrity seamlessly.

Company policy

The truth is in the numbers

0B+

Prompts and responses

0 Milliseconds

Guardrails latency

0%

Of hallucinations are detected and mitigated before impacting your users.

From security to hallucinations

End-to-end control
for your AI apps

4.8 out of 5 stars

See All reviews
Designed For Engineers

Add GenAI Guardrails with a single API call.

With Aporia’s detection engine you’ll always have the latest safeguards against hallucinations and prompt injections attacks. This means you can focus on making great LLM-based apps, without the hassle of implementing new hallucination mitigation methods every 2 weeks.

Docs
self._client = openai.OpenAI(

    api_key = "openai-api-key"

    base_url="aporia-guardrails-endpoint"

)
import requests



response = requests.post(

    f"{GUARDRAILS_ENDPOINT}/validate",

    json={

        "messages": [

            {"role": "system", "content": "You are a helpful assistant."},

            {"role": "user", "content": "hello world!"},

        ],

        "response": "Hi! How can I help you?",

    },

)

# response = {"action": "block", "revised_response": "Blocked due to off-topic response"}
response = await fetch(`${GUARDRAILS_ENDPOINT}/validate`, {

  method: "POST",

  headers: {

    "Content-Type": "application/json",

  },

  body: JSON.stringify({

    messages: [

      { role: "system", content: "You are a helpful assistant." },

      { role: "user", content: "hello world!" },

    ],

    response: "Hi! How can I help you?",

  }),

});

response = await response.json();
// response = {"action": "block", "revised_response": "Blocked due to off-topic response"}

Integrates in minutes

Either call our REST API or just change your your base URL to an OpenAI-compatible proxy.

Works with any LLM

Whether you are using GPT-X, Claude, Bard, LLaMA or your own LLM, Aporia is designed to fit seamlessly into your current setup.

Specialized LLM
use-case support

• RAG chatbot
• Text-to-SQL
• Structured data extraction
• Data enrichment
• Summarization

Battle-tested for
the Enterprise

New apps gain automatic guardrails and policy customization via the centralized AI gateway.

Platform overview

Supported Safeguards

Safety
out of the box
custom
Tonality
Detect and prevent responses that don’t align with desired tonality
Toxicity
Provides detection and interception of toxic
inputs and outputs
PII (Privacy Filtering)
Detects and prevents transmission of PII
 including 20 types of data
Groundedness
Detect hallucinations and validate information returned from the model based on RAG injected content
Security
out of the box
custom
Prompt Injection
Protect against prompt injections that can lead to harms
Jailbreaks
Provides robustness testing, fine-tuning, prevention of common hacking attempts, and protection against harms
IP and Confidentiality
Protect against IP leakage and confidential information
Brand Protection
Customized brand protection
Bias
out of the box
custom
Stereotypical Bias
Detect bias inputs and training data that has been incorporated into the base model
Ethical Filtering Rules
Provide additional context to ensure context
appropriate responses
Custom
out of the box
custom
Topicality
Define topics that models should be allowed or exclude from conversations
Custom Fact-Checking
Provides a framework for detecting hallucinations and validating information returned from the model
Compliance Checks
Checks against regulations and internal policies to ensure compliance
Build your own
Add your own alignment controls and mitigation strategies to ensure your models performance and safety
Don't let AI risks damage your brand

Control all your AI Apps in Minutes

“In a space that is developing fast and offerings multiple competing solutions, Aporia’s platform is full of great features and they consistently adopt sensible, intuitive approaches to managing the variety of models, datasets and deployment workflows that characterize most ML projects. They actively seek feedback and are quick to implement solutions to address pain points and meet needs as they arise.”

Felix D.

Principal, MLOps & Data Engineering

“As a company with AI at its core, we take our models in production seriously. Aporia allows us to gain full visibility into our models' performance and take full control of it."

Orr Shilon

ML Engineering Team Lead

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“ML models are sensitive when it comes to application production data. This unique quality of AI necessitates a dedicated monitoring system to ensure their reliability. I anticipate that similar to application production workloads, monitoring ML models will – and should – become an industry standard.”

Aviram Cohen

VP R&D

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“With Aporia's customizable ML monitoring, data science teams can easily build ML monitoring that fits their unique models and use cases. This is key to ensuring models are benefiting their organizations as intended. This truly is the next generation of MLOps observability.”

Guy Fighel

General Manager AIOps

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“ML predictions are becoming more and more critical in the business flow. While training and benchmarking are fairly standardized, real-time production monitoring is still a visibility black hole. Monitoring ML models is as essential as monitoring your server’s response time. Aporia tackles this challenge head on.”

Daniel Sirota

Co-Founder | VP R&D

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