Trustworthy AI for Businesses
Reliath AI has developed a patent-pending alternative to Generative AI: the world’s first AI truth platform. Designed for transparency and trust, Reliath AI is a flexible SaaS solution that can also be deployed on-premises or within Docker containers. It serves as a foundational platform for businesses seeking reliable, verifiable, and accountable artificial intelligence.
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The Problem with Generative AI
Large Language Models are word guessers. They don’t know truth — they only predict tokens. That’s why they hallucinate and fail enterprises.
Scale
AI companies mistakenly believe that scaling compute and data will fix the problem, but this approach is economically unsustainable and ineffective.
Hallucinations
Hallucinations are inevitable because models don’t understand truth — they only predict likely words, not facts.
Guardrails
Filters and “guardrails” only mask the issue of misalignment. They remain fragile, costly, and easy to bypass.
RAG
Complex RAG systems meant to improve accuracy often fail due to multi-step, error-prone processes.
Continuous Learning
Today’s language models are unable to learn continuously – updates require costly ad-hoc retraining that’s unsustainable.
Reasoning
What’s called “reasoning” in AI is just pattern imitation without real understanding or causal logic.
Data Pollution
Models are polluted by synthetic and low-quality data, leading to degradation and loss of diversity.
Anthropogenic Debt
AI still relies heavily on human labor — labeling, checking, and tuning — creating massive time and cost burdens.
A New
Paradigm for AI
Reliath shifts the unit of analysis from tokens to facts. We build Truth Profiles — the DNA of truth for AI. This separates verified from hypothetical and ensures only trustworthy outputs.
Detect & prevent hallucinations
Reliath distinguishes facts from fabrications, storing them in a proprietary logical/semantic form.
Dynamic Learning
Single-pass, online learning. Compact, energy-efficient models.
Enterprise-ready & private
Works on customer’s own data. No leakage, no cross-training. SaaS or on-prem.
Energy Efficient
Compact models that use only a fraction of what's required to run language models.
Use Cases
Real-world use cases where Reliath adds a Truth Layer to AI — from compliance and healthcare to customer service and research.
Solving AI’s Hallucination Problem
Learn how Reliath addresses the key problem of artificial intelligence — hallucinations. This white paper explains the Truth Profiles technology, real-world applications, and business benefits.
Detect & prevent AI hallucinations
Truth Profiles & Knowledge Graph explained
Industries that gain with Reliath
The new standard for enterprise AI
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FAQ
Reliath shifts the unit of analysis: from tokens to factoids and facts. We build Truth Profiles — the DNA of truth for AI. This separates verified from hypothetical and ensures only trustworthy outputs.
How is Reliath AI different from incumbent GenAI models?
Intelligence starts with facts. Incumbent GenAI Large Language Models are token predictors, with no way to distinguish fact from fiction. Any text that matches their learned statistical model is equally valid. According to OpenAI, hallucinations by these models are inevitable. According to Anthropic, these models cannot be trusted. Reliath AI solves these problems by modeling verifiable, auditable, trustworthy facts using a proprietary logical/semantic representation.
What is Reliath AI?
Reliath AI is a company that has invented a new paradigm in artificial intelligence. Reliath AI addresses and eliminates the root cause of AI hallucinations. For Reliath AI the most basic element is the factoid, not tokens. A token, such as “purple” cannot be either true or false. But a simple statement, such as “The sky is purple,” could be true or it could be false. Reliath AI represents those truth-carrying elements as a dual combining the abstract logical relations expressed in the phrase with continuous semantic elements, thus taking advantage of strengths of both types of representations.
Is Reliath AI just another application built on top of an LLM?
No. Reliath AI is its own kind of fact model, not a language model. The basic unit of analysis is the factoid, not a token. Reliath AI is a foundation model on which applications are built. Just as there are thousands of applications that have been built on top of LLMs (such as GPT), we anticipate that there will be thousands of applications built on the Reliath AI foundation, each serving its own specific market need. Reliath AI provides this foundation as a SaaS model, or as a container for on-prem service.
Who provides the source of truth to the Reliath AI model?
Each customer gets its own Reliath AI model, establishing its own source of truth. As a result, each model is bespoke for each customer and there is no sharing of data between models, no data leakage, and no inappropriate content.
Does the Reliath model scale?
The short answer is yes. The Reliath AI model requires minimal computational resources, it learns in one pass through the data so that it is very quick to train and very quick to access. It requires minimum human effort to identify the initial sources of truth. It requires no reinforcement learning through human feedback, no data labeling. Compared to the time and money it takes to train GenAI models, label data, provide guardrails, and so on, the cost to run Reliath AI is little more than roundoff error.
