Enhance LLM performance

Hallucinations Mitigation

Carve out your competitive edge and fast track your Gen-AI to production, ensuring every LLM response is clear, reliable, and on target. 

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Are hallucinations undermining your LLM’s trustworthiness?

Over 86% of organizations report an ongoing battle against hallucinations. Hallucinations can skew your model’s outputs, making it produce factually incorrect, NSFW, or nonsensical results. This reduces confidence in your Gen-AI product and compromises user experience and brand trust.

Mitigating hallucinated responses in real time

Ensuring trusted & consistent LLM interactions in real time

  • Aporia is layered between your LLM and your GenAI interface, mitigating hallucinated responses in real time.
  • Integrate Aporia with all of your LLMs (API-based, or otherwise) and activate hallucination mitigation in minutes.
  • Access real-time hallucination scores and mitigation techniques within the same platform.
  • Identify inconsistencies, verify knowledge, and ensure AI reliability instantly.

Response consistency & analysis

More than just simple output checks

  • Leverage continuously updated hallucination mitigation techniques, bridging the latest benchmarks and Langchain role-based libraries into real-world LLM performance.
  • Deeply analyze LLM outputs through techniques like SelfCheckGPT and specialized RAGs support.
  • Improve AI accuracy, minimize hallucinations, and unlock new dimensions of trust and efficiency.

Drive confidence, deploy faster

Ensure your GenAI product is actually being used

  • Fast-track deployment while guaranteeing reliable, high performing GenAI products.
  • Free ML teams to focus on core application development and reduce your spend in the manual battle against hallucinations.

Insights, oversight & analytics

Don’t settle for basic data mapping

  • Centralize LLM activity to effortlessly track and analyze hallucinations and trends across segments over time.
  • Deep dive into any chat session, and pinpoint the original and corrected responses against detected hallucinations.
  • Ensure relevance, address context, and prevent your AI from relying on random texts.
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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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