Mihai Cotocel Launches AdverseMe, Bringing AI-Assisted Screening to Compliance Teams
The founder brings more than 15 years of enterprise technology experience to a platform combining source evidence, four AI judges and human review. AdverseMe reports three signed agreements.
Mihai Cotocel, a technology executive with more than 15 years of experience in enterprise IT, cybersecurity and digital transformation, launched AdverseMe on September 1, 2026. The UAE-based screening software business reports that three organizations have signed agreements with the company.
Cotocel's professional background spans IT strategy, services and infrastructure aligned with business needs, as well as security and risk management across enterprise and cloud environments. His work also includes enterprise systems, cloud migration and practical process automation. This operational and security experience provides the background to his work as the founder of AdverseMe.
His work connects enterprise technology, process automation and the practical use of AI in screening workflows. AdverseMe applies AI to assessing collected evidence and presenting reasoning for human review. More about Cotocel's professional background is available at https://mihaicotocel.com/.
The platform covers four screening areas: sanctions, politically exposed person (PEP) exposure, adverse media and ownership. It brings together source searches, identity review, AI-assisted assessments and reports, giving compliance teams a record of the information considered when reviewing people and companies.
A central capability is the use of four independent AI judges to assess retained findings. The system records their reasoning and disagreement and uses the median of available scores. Reviewers can examine the evidence alongside the assessment, including differences between the models. Agreement among AI judges does not eliminate the possibility of shared errors, and the final decision remains with a human reviewer.
Identity review helps distinguish the supplied person or company from namesakes. Source references, excluded matches and coverage limitations remain part of the record. The source trace distinguishes a completed search returning no retained match from a source that was unavailable or skipped, helping reviewers understand what the screening covered and where further investigation may be needed.
Teams can screen individual subjects in the application, process CSV batches or connect their own systems through a REST API. These three delivery modes support direct use of the software and integration into existing operational processes. Product information and the published methodology are available at https://adverseme.com/.
A result showing no retained match does not establish that a subject is risk-free. AdverseMe supports evidence collection and assessment; the responsible team retains decisions about onboarding, further investigation and ongoing business relationships.
Cotocel's professional background spans IT strategy, services and infrastructure aligned with business needs, as well as security and risk management across enterprise and cloud environments. His work also includes enterprise systems, cloud migration and practical process automation. This operational and security experience provides the background to his work as the founder of AdverseMe.
His work connects enterprise technology, process automation and the practical use of AI in screening workflows. AdverseMe applies AI to assessing collected evidence and presenting reasoning for human review. More about Cotocel's professional background is available at https://mihaicotocel.com/.
The platform covers four screening areas: sanctions, politically exposed person (PEP) exposure, adverse media and ownership. It brings together source searches, identity review, AI-assisted assessments and reports, giving compliance teams a record of the information considered when reviewing people and companies.
A central capability is the use of four independent AI judges to assess retained findings. The system records their reasoning and disagreement and uses the median of available scores. Reviewers can examine the evidence alongside the assessment, including differences between the models. Agreement among AI judges does not eliminate the possibility of shared errors, and the final decision remains with a human reviewer.
Identity review helps distinguish the supplied person or company from namesakes. Source references, excluded matches and coverage limitations remain part of the record. The source trace distinguishes a completed search returning no retained match from a source that was unavailable or skipped, helping reviewers understand what the screening covered and where further investigation may be needed.
Teams can screen individual subjects in the application, process CSV batches or connect their own systems through a REST API. These three delivery modes support direct use of the software and integration into existing operational processes. Product information and the published methodology are available at https://adverseme.com/.
A result showing no retained match does not establish that a subject is risk-free. AdverseMe supports evidence collection and assessment; the responsible team retains decisions about onboarding, further investigation and ongoing business relationships.
- Contact Email
- [email protected]
- Issued By
- AdverseMe
- Business Address
- P.O. Box 124121
Dubai, United Arab Emirates - Country
- United Arab Emirates
- Categories
- Finance · Software · Technology
- Last Updated
- September 15, 2026