Dryfta Introduces Virtual Reviewers and AI Assisted Document Scanner for Smarter Abstract Management

At IMEX 2026, Dryfta is presenting two important additions to its abstract management software: Virtual Reviewers for AI assisted peer review and an AI assisted document scanner designed to improve submission quality before and during the review process.

These latest updates are built for conference organizers, scientific societies, associations, and institutions that manage large volumes of abstracts and need a more scalable, structured, and reliable review workflow.

Dryfta has long helped event organizers manage abstract submissions, reviewer assignments, scoring, decisions, speaker communication, and program building from one platform. With these new AI assisted capabilities, Dryfta is taking the next step by helping organizers strengthen review quality, reduce repetitive manual effort, and support human reviewers without replacing them.

Virtual Reviewers that work like real reviewer profiles

Dryfta now allows administrators to enable AI Reviewers directly from the submission settings under review settings. Once enabled, organizers can create up to three Virtual Reviewers. These Virtual Reviewers appear in the Manage Reviewers area just like human reviewer profiles and can be edited or deleted at any time.

Each Virtual Reviewer can be configured with its own profile and review behavior. Organizers can define areas such as:

• topic expertise
• track expertise
• submission type preference
• language preference
• reviewer role or affiliation
• mapped custom fields
• informative fields that should be ignored during review

By default, all topics, tracks, and submission types can be assigned to each Virtual Reviewer at creation. Administrators can then fine tune the profile based on the needs of the event, the subject matter, and the structure of the review process.

This gives organizers the flexibility to create AI reviewers that behave differently from one another. For example, one Virtual Reviewer may be tuned for Biology abstracts in French, while another may be configured for clinical research in English or for industry oriented submissions under a different track.

Reviews based on expertise fit, language, and profile context

Virtual Reviewers are assigned submissions based on the data saved in their reviewer profile. This includes topic fit, affiliation context, language preference, submission type, and other mapped attributes.

Importantly, Dryfta does not apply human reviewer workload limits to Virtual Reviewers. This ensures that every submission can still benefit from AI assisted analysis, even when human reviewer capacity is limited.

Once assigned, the Virtual Reviewer scans the submission and reviews it in line with its configured reviewer profile. If the profile is tuned for a specific language, discipline, or expertise area, the AI review is expected to follow that context. 

AI assisted document scanner adds an early quality layer

Alongside Virtual Reviewers, Dryfta is also introducing an AI assisted document scanner for abstract management workflows.

This scanner helps evaluate whether a submission is review ready before it moves deeper into the peer review process. It can identify low quality content such as:

• dummy text
• incomplete or empty fields
• poorly structured submissions
• content that appears irrelevant to the selected topic / track
• content issues that make evaluation difficult

When a submission does not meet a reasonable threshold for assessment, the Virtual Reviewer is not forced to submit an artificial score. Instead, it can abstain and return a clear reason, such as:

• abstained due to low expertise fit
• abstained due to unsupported language

This is an important distinction. Rather than generating unreliable ratings where confidence is weak, Dryfta’s AI assisted workflow is designed to behave responsibly and transparently.

Advisory only; human decisions kept separate

Dryfta has designed Virtual Reviewers to support the review process, not override it.

All scores and comments submitted by Virtual Reviewers are stored in the system in the same format as normal review data, but virtual scores remain strictly separate from human scores. Virtual reviews do not alter the overall abstract rating and are used for advisory purposes only.

This allows scientific committees and program teams to benefit from AI generated insight while protecting the integrity of human led decision making. To make this distinction even clearer, Dryfta is adding separate list view columns that display:

• cumulative rating from Virtual Reviewers
• cumulative rating from human reviewers

This gives organizers a clean side by side view without mixing the two.

Built for speed, consistency, and better review oversight

For conferences managing hundreds or thousands of submissions, these updates can make a meaningful difference. Virtual Reviewers can help flag issues earlier, support reviewer assignment logic, reduce avoidable review effort, and provide a second layer of analysis at scale.

At the same time, organizers remain fully in control. Human reviewers continue to make the real evaluation decisions, while AI contributes structured, profile based, and clearly separated advisory input.

With these updates, Dryfta continues to expand its abstract management software into a more intelligent and practical solution for modern conferences, helping organizers run fairer, faster, and more informed review processes.