Halluminate provides an API-based testing layer for AI agents, enabling the creation and fine-tuning of application-specific evaluation models that assess AI outputs against defined criteria. This solution reduces the engineering time spent on manual testing by 90%, addressing the inefficiencies and performance degradation associated with traditional deployment practices.
Funding
$30K raised to dateRaised 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.


Founders
Product
Problem
Manually testing AI agent outputs requires significant engineering time, especially given the unique testing criteria for each AI application. This leads to inefficiencies and delays in deployment.
Solution
Halluminate offers an API-based evaluation layer for AI agents, enabling the creation, fine-tuning, and deployment of application-specific evaluation models. These models assess AI outputs against defined criteria, providing confidence scores and reducing manual testing time by up to 90%. The platform allows users to define custom testing requirements, such as accuracy, structure, and data security, and integrates seamlessly with existing observability platforms and codebases. By aligning evaluation model judgments with annotated labels, Halluminate improves correlation with human graders, ensuring trustworthy results.
Target Audience
Halluminate primarily targets AI/ML engineers and developers building applications with AI agents who need to automate and streamline the evaluation process.
Features
- API-based endpoint for easy integration with existing systems
- UI-based playground for crafting custom grading rubrics
- Ability to define custom testing requirements, including accuracy, structure, and data security/PII
- Evaluation model alignment with human graders for improved trustworthiness
- Confidence scores for AI-generated outputs
- Support for various evaluation criteria, including truthfulness, consistency, and data leakage