CEO
AUI™ (Augmented Intelligence
Develops a neuro-symbolic AI language model that combines the conversational capabilities of generative AI with the predictability and tool-use efficiency of rule-based systems. This architecture reduces errors by 95% compared to transformer-based agents and enables businesses to create highly accurate, steerable AI agents that integrate seamlessly with existing tools and workflows.
- Artificial Intelligence
- Developer Tools
- Enterprise Software
- Software Only
Updated 7 months ago
Funding
Raised to date
$43.2MRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
$30M across 2 disclosed rounds
EVESSP$20M · Bridge
Announced Nov 2025
Disclosed cumulative: $30M
2/2
Reported total $43.2M
Incomplete round history. $13.2M of the $43.2M reported total isn’t matched to a known round.
RoundDateAmountValuationInvestors
Founders
Product
Problem
Traditional transformer-based language models often struggle with tool use, predictability, and steerability when deployed as AI agents for business applications. These models can be prone to errors and hallucinations, limiting their effectiveness in real-world scenarios requiring accuracy and reliability.
Solution
AUI's Apollo is a neuro-symbolic AI language model designed specifically for building reliable and steerable AI agents. By combining the conversational capabilities of generative AI with the predictability of rule-based systems, Apollo significantly reduces errors and hallucinations compared to traditional transformer-based models. This architecture enables businesses to create AI agents that can seamlessly integrate with existing tools and workflows, providing a guided experience with guardrails and grounded responses. Apollo-based agents demonstrate improved accuracy and success in tool use, making them suitable for complex business tasks.
Target Audience
The primary target audience includes businesses seeking to deploy highly accurate and reliable AI agents for customer service, automation, and other business-critical applications.
Features
- Neuro-symbolic architecture combining generative AI with rule-based systems
- Enhanced tool use capabilities compared to transformer-based LLMs
- Improved steerability and predictability for reliable agent behavior
- Reduced error rate compared to traditional language models
- Seamless integration with existing business tools and workflows
- Guided experience with built-in guardrails