AutoAlign Knowledge Bases Create Comprehensive Generative AI Fact-Checking

Generative AI continues to revolutionize how we access and interact with information. As such, ensuring large language models (LLMs) provide accurate, reliable information remains paramount. At AutoAlign, we’re dedicated to making generative AI safe and effective. In that spirit, we recently unveiled a groundbreaking innovation: AutoAlign Knowledge Bases. 

This advancement proves especially crucial in domains where misinformation is harmful. These might be important scientific, industrial, or societal topics. We created a general Knowledge Base available for our enterprise users, so they have these data repositories to ensure generative AI answers are highly factual. Enterprises can now also easily create their Knowledge Bases so models can provide the best, most accurate solutions to their employees and customers. Best of all, these knowledge bases can work seamlessly with existing RAG solutions or can be loosely coupled as a powerful fact-checking layer. Look out for more AutoAlign Knowledge Bases across other critical topics.  

We also wanted to build Knowledge Bases that address societal needs by curbing misinformation’s spread and its ability to impact public discourse. With the election underway, having accurate information is critical for informed decision-making, which is why we decided to create the Election Knowledge Base.

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AI Responses: Accuracy is Critical

Generative AI's potential to answer complex questions factually, without bias, and without evasion is essential — particularly during election seasons. However, it’s not working out so seamlessly. For example, right now major models are supplying false information about election voting, as well as simply not answering potentially controversial questions factually — a symptom of over-tuning. Misinformation, or a lack of information, can significantly influence public opinion as well as election outcomes. AutoAlign Knowledge Bases combat misinformation and deliver precise, accurate answers on even the most controversial topics, continually ensuring the integrity of AI-generated information.

Sidecar’s Unique Approach

AutoAlign's Sidecar is a dynamic firewall that is set up to run alongside major generative AI models. Sidecar technology runs alongside LLMs and provides consistent security by dynamically interacting with models. Traditional methods either restrict model responses or risk introducing biases. In contrast, Sidecar enhances model accuracy and reliability without these drawbacks. We proved this safety and performance duality in our recently released white paper that includes findings from our integration into NVIDIA’s NeMo Guardrail system. For the full report, please look here: https://bit.ly/AutoAlignWhitePaper 

Sidecar includes advanced and fully integrated Alignment Controls, which allow users to set their own security and accuracy parameters. It works seamlessly with every major AI model like OpenAI’s GPT-4o, Anthropic’s Claude 3.5 Sonnet, Google’s Gemini 1.5, and more. These Alignment Controls include off-the-shelf data leakage prevention, toxicity filtering, fact-checking, and more, as well as the ability to build custom parameters for specific use cases.

Election Knowledge Base

By detecting and mitigating incorrect answers in real-time, Sidecar ensures AI models deliver accurate and reliable information. At VentureBeat Transform 2024 in San Francisco, our CEO and co-founder Dan Adamson introduced AutoAlign’s Election Knowledge Base during the Innovation Showcase. This is the first consumer knowledge base integrated with Sidecar that provides accurate, fact-checked answers to election-related queries. For instance, when asked about voting registration laws in Pennsylvania, ChatGPT hallucinated the wrong answer. However, when the model was affixed with Sidecar, which had the Election Knowledge Base turned, it mitigated the incorrect answer. It delivered a factual one by distinguishing between legal facts and public opinion. Here’s our CEO presenting these findings in front of AI leaders in San Francisco. 

By leveraging the Election Knowledge Base, Sidecar also addresses controversial questions with factual precision. What this means practically is that any mitigated response that Sidecar fact-checks, is annotated with pieces of evidence that anyone can trace to ensure transparency. This capability proves vital in ensuring reliable information during the election season, as well as allowing Sidecar to leverage more Knowledge Bases that maintain information integrity for other topics.

To learn about how Sidecar’s LLM security, including AutoAlign’s new Knowledge Bases, can make your enterprise generative AI accurate and powerful, book a demo today: https://www.autoalign.ai/demo

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