Secure LLM Performance

Prompt Injection Prevention

Filter out malicious input before it compromises your LLM, ensuring prompt integrity and reliable performance.

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Crafting Gen-AI products is an art, but prompt injections destroy the canvas

Prompt injections can distort your model’s outputs, turning it into a puppet to malicious intents. This erodes your end user’s trust in your Gen-AI product and potentially results in misinformation, misuse or data leakage, compromising the true integrity, purpose, and reliability of your LLM.

Mitigate threats before they strike

Enhancing security with smart insights

  • AI Guardrails acts as a middle layer and prevents prompt injections from getting to your LLM and retraining it.
  • Boost your security by preventing malicious inputs from touching your LLM.
  • Mitigate potential risks to maintain LLM integrity with minimal manual intervention.
  • Improve overall system resilience by minimizing vulnerabilities.

Tailor PIP to your needs

Gain full control over the Guardrails that protect your LLM. First test and then act.

  • Start by observing flagged prompts without affecting the system and transition seamlessly to ensure safety when you feel it’s time.
  • Tailor Guardrails for maximum efficacy and minimal intrusion.

Double up on defense by learning from the past

Harnessing dual LLM detection & historical insights

  • Utilize a secondary LLM to analyze prompts, while your primary model remains focused and undisturbed by potential threats.
  • Strengthen your defenses by converting each past attack into a lesson, ensuring an adaptive and resilient system.
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“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

“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

“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

“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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