
Aayush Bhan
Agentic AI Engineer
Integrity.Tell authentic content from synthetic or false claims before they spread.

AI Information Integrity.
Detect AI-generated misinformation
False claims produced by a model spread before anyone flags them.
Reduce false information generation
The system produces false claims a reader will treat as fact.
Prevent AI amplification of false claims
Ranking, summaries, or agents give false claims more reach.
Verify AI-generated claims
Generated claims are published with no source check.
Detect deepfakes
Synthetic faces, voices, or scenes pass as recordings of real people.
Authenticate images
A viewer cannot tell whether an image is a photograph or a generation.
Authenticate audio
A listener cannot tell whether a voice recording is real.
Authenticate video
A viewer cannot tell whether the footage happened.
Detect AI-powered persuasion
Persuasive systems steer people without a visible sign.
Prevent targeted manipulation
Messages are tailored to a person weaknesses.
Detect coordinated influence
Many accounts or agents push one narrative and look organic.
Protect vulnerable users
People who are easier to mislead get no extra protection.
Verify content origin
Content is shared with no way to check who made it.
Track content transformations
Crops, edits, and model passes erase the path from the original.
Establish authenticity
There is no reliable way to show a piece of content is authentic.
Maintain provenance across platforms
Origin data is stripped when content is reposted.
Measure AI amplification effects
Automated ranking and generation crowd out slower, sourced information.
Detect search manipulation
Search results are steered by synthetic or gamed content.
Detect recommendation manipulation
Recommendations are pushed off what the user asked to see.
Reduce synthetic content saturation
Feeds and search fill with generated content until real sources are hard to find.
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