Do you trust AI?
Every day, billions of sentences appear in AI chatbots, news, podcasts, and social media. Factiverse Claim Detection understands, verifies, and detects AI failures early, so teams can evaluate models, reduce risk, and align them with evidence.
The same technology checks the claims in your video, audio, and text sources.
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In daily production with Nordic government customers. Independently security-tested at a NATO-certified centre.
WHERE YOU FIT
Built for AI model builders, defence, and media.
Pick the work you are responsible for and we will take you to the part of Factiverse built for it.
Builders and Sovereign AI
Find AI failures in seconds and prove your model holds up in smaller languages, on the topics that carry risk.
Defence and intelligence
Collect open sources at volume and see how every outlet reports the same story, with each claim tested against sources you trust.
Media and research
Understand harmful narratives before they reach the wider public, across broadcast, podcast, and social media.
Find clarity
LLMs generate sentences. We understand them.
Billions of sentences are generated every day in AI chatbots, news, podcasts, and social media, and no one can manually verify them. This leads to the rapid spread of factual and numerical errors, especially when AI falls into the hands of malicious actors.
Faster and more precise than any LLM today, Factiverse can separate noise from factual claims, check them against evidence, and show which ones could put your company at risk. In 114 languages.
As seen in
Why now
We started with AI safety B.C. - Before ChatGPT.
We are old-school machine learning and natural language processing, starting as award-winning university research in 2015.
Today, we have peer-reviewed research and benchmarks showing that we outperform leading SLMs and LLMs on crucial benchmarks that will be integral to the future of Internet infrastructure. Our strong partnerships, our team's background in trust, safety, and democracy, and our large, unique corpus of human-annotated data and proprietary models are the reason we built this.
The proof
Faster and cheaper, with no trade-off in accuracy.
FACTIVERSE VS FRONTIER MODELS IN CLAIM DETECTION
CLAUDE / GEMINI API COSTS (APPROX)
Factiverse
Speed
Time to analyse the pasted text
29 to 50 minutes
1.3 seconds
Roughly 1,400 times faster
Energy/Environmental Cost
Per analysis of the same text
$4.36
2000x more cost effective
Specific estimations on request
Accuracy
Across 114 languages
Baseline
Matched or better
with no trade-off.
CLAUDE / GEMINI API COSTS (APPROX)
Factiverse
Speed
Time to analyse the pasted text
7 hours
13 seconds
Roughly 1,400 times faster
Energy/Environmental Cost
Per analysis of the same text
$43.60
2000x more cost effective
Specific estimations on request
Accuracy
Across 114 languages
Baseline
Matched or better
with no trade-off.
CLAUDE / GEMINI API COSTS (APPROX)
Factiverse
Speed
Time to analyse the pasted text
3 days
2 minutes
Roughly 1,400 times faster
Cost
Per analysis of the same text
$436.00
2000x more cost effective
Specific estimations on request
Accuracy
Across 114 languages
Baseline
Matched or better
with no trade-off.
CLAUDE / GEMINI API COSTS (APPROX)
Factiverse
Speed
Time to analyse the pasted text
27 days
22 minutes
Roughly 1,400 times faster
Energy/Environmental Cost
Per analysis of the same text
$4,360.00
2000x more cost effective
Specific estimations on request
Accuracy
Across 114 languages
Baseline
Matched or better
with no trade-off.
Our approach
What we do
Identifying claims in different media and information tools and verifying against trusted user sources
LLMs & SLMs
Models can easily stumble into producing false or harmful answers under specific and targeted prompts.
Our LLM Audit methodology and claim detection technology surface these failures to industry experts to review and produce the training data model providers to fix them.
Our LLM Audit methodology and claim detection technology surface these failures to industry experts to review and produce the training data model providers to fix them.
Audio and video
Content in broadcasts, YouTube and TikTok push controversial claims about current elections, conflicts and policy.
Gather analyses this content 10x faster than it takes a person to watch it. Giving users an overview of claims on important topics across 114 languages.
Gather analyses this content 10x faster than it takes a person to watch it. Giving users an overview of claims on important topics across 114 languages.
Text
Textual content on messaging apps, websites and research documents is being produced that normal LLMs cannot effectively handle.
Our models can effectively process millions of sentence to deliver back controversial claims and narratives judged against user trusted sources.
Our models can effectively process millions of sentence to deliver back controversial claims and narratives judged against user trusted sources.
Testimonials
Trusted by the teams building the future of information.
Political content doesn't wait for you to catch up. Before this Factiverse integration, fact-checking and monitoring political video at scale simply wasn't possible. Now it is — and it works directly inside the Renki workflow our journalists already use every day.
Taru Salo
Head of Digital Development, Data & AI, Viestimedia
The data provided by Factiverse was extremely useful for our outlet in identifying the key Ukraine- and Russia-related narratives circulating in the Czech media space ahead of the parliamentary elections. A major benefit was how efficiently the report helped us pinpoint the key narratives, saving us valuable time in the process and guiding the further focus of our research.
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Martin Fornusek
Senior News Editor, The Kyiv Independent
Even with five people on the team, Factiverse was able to pick up claims from the debates that we missed. The transcript had an accuracy of almost 95%, and sometimes the fact-checks happened as they were spoken. This solution has immense potential and already saves us a lot of time
Thomas Hedin
Editor-in-Chief, Tjekdet
Without more organised cooperation, stronger editorial expertise, and new tools such as Factiverse AI, Finnish media cannot keep up with what is happening around them and in the digital world
Joonas Pörsti
Editor-in-Chief, FactBar
Our origin
Kjeller, 1973
In 1973, the internet left America for the first time. It came to Norway. The connection ran out of a defence lab outside Oslo, set up to check whether a nuclear treaty was being kept.
The first thing the international internet did was check a claim.
We believe the solution for the AI trust infrastructure will come from Norway.
It is a country with the highest newspaper density per capita in the world, more than 200 government-subsidised local papers, and a top annual ranking on freedom of speech. Norway has spent a century building trust between people and institutions, and it creates a different framework for how we build technology with a focus on ethics, trust and accountability.
By the way
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