Fewer than half of people who use artificial intelligence say they trust it, and that figure has grown over the past three years, according to a recent global survey of 48,000 consumers. Now, startup IndagoAI LLC is tackling that issue with today’s announcement of its Trust Solutions Platform.

It’s a suite of tools aimed at improving confidence in AI-generated research by rating its accuracy and credibility across a broad range of criteria. The firm’s TrustScore is a patent-pending algorithm that applies more than a dozen trust “themes” and 60 factors to evaluate the reliability of research findings in industries such as biopharma, construction, publishing and standards organizations.

The company said its goal is to mitigate the growing problem of AI-generated “hallucinations,” or fabricated facts presented as true information, by providing enterprises with a standardized method to assess the trustworthiness of research outputs.

Hallucination detector

Christian Mairhofer, IndagoAI’s co-founder and chief operating officer, said hallucination detection is built directly into the platform. “If you include multiple [large language models] in your research, you don’t know which is true,” he said. “This is a way of quickly seeing if research is bogus because it doesn’t have any content behind it.”

TrustScore evaluates documents, data sources and AI-generated outputs across multiple dimensions, including authorship, objectivity, source credibility, numerical soundness and bias. Scores are generated on a scale of 1 to 10, accompanied by detailed commentary that explains the reasoning behind each rating.

The system draws upon both internal analysis and external validation. For example, it assesses the source’s citation frequency, its reliance on credible publications and the frequency with which independent outlets have corroborated claims. The platform can also analyze multiple documents simultaneously, providing organizations with an overall trust assessment for large-scale research projects.

The methodology reflects two years of work with library science experts and enterprise clients who needed a more reliable way to integrate private and public data into research workflows, said Jim King, IndagoAI’s co-founder and chief executive.

“Trust is not just a single feature. Trust is based on a nuanced understanding of what goes into creating information,” King said. “We look at whether an article presents emotionally charged language or factual claims, whether it cites credible sources, how it has been received publicly and whether statistical claims stand up to scrutiny.”

Better decisions

Mairhofer said TrustScore is designed to integrate into existing enterprise research systems. “If you research 20, 30 or 40 articles, you can have an overall trust score for your research project as well,” he said. “By reinforcing confidence in research results, we can help companies make better decisions with greater transparency.”

Organizations can customize the weighting of factors to align with industry-specific requirements. For example, biopharma firms may prioritize clinical trial data verification, while financial institutions emphasize real-time information accuracy and regulatory compliance.

The company plans to offer both enterprise-wide dashboards and consumer-facing versions of TrustScore. It also hopes to integrate with standards organizations to create industry-wide benchmarks for content credibility.

King and Mairhofer, who are both veteran executives at large technology firms, founded IndagoAI in 2023. The company has raised unspecified seed funding and is generating revenue from early deployments of its platform in biopharma, construction, and standards markets.

Plans include expanding integrations with third-party data sources, adding plagiarism and AI-generated content detection and offering small-business and consumer versions of TrustScore.

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