Better context for site strategy.
Investigator experience, enrollment history, study burden, staffing and capacity inform AI-assisted site assessment and study-specific recommendations.
Explore Real Time IntelligenceMore clarity in the details.
More purpose in every decision.
Our proprietary technology brings AI into the daily work of clinical research—from evaluating study documents to surfacing temperature-log exceptions. Built to inform your team. Guided by experienced people.
The difference is in what your team can see—and act on.
InFocus has validated and deployed AI workflows for eTMF document evaluation and temperature-log review. They organize complex information, surface potential issues and give reviewers a more focused starting point.
Every study document carries more than its contents. It has a purpose, a history and a place in the study record.
Using ALCOA++ as its evaluation guideline, InFocus AI Validation produces a document score and summary, flags critical findings and warnings, and recommends next steps. It also recognizes metadata and suggests relationships to people, visits and study records.
A structured starting point for human quality review, with potential issues and filing context brought into focus.
Reviewers assess the findings, confirm recognized metadata and make approval decisions.
| Site | Period 1 | Period 2 | Period 3 |
|---|---|---|---|
| Site A | Received | Excursion | Received |
| Site B | Missing days | Missing log | Both flags |
| Site C | Inactive | Inactive | Received |
Follow the finding back to the file.
Associated documents and findings are available for each tracker cell.
Temperature logs can be present and still contain significant issues. Our dedicated AI evaluation goes beyond file collection to examine the information inside.
A single dashboard provides a clear view of temperature monitoring across your study. Quickly spot missing logs, gaps in daily records, and temperature excursions—with each site tracked throughout its active period, so your team can focus on what needs attention.
A clearer basis for targeted follow-up, with source files and findings together for your team to investigate.
Technology assists. Experienced professionals review, interpret and approve. That principle is built into how we use AI—not added at the end.
Evaluate information, recognize context and flag potential issues.
Assess findings, verify metadata and consider the clinical and operational context.
Approve the record or direct the appropriate follow-up.
Our tech stack is the collection of platforms and tools that supports your study. Proprietary eVision, Real Time Intelligence (RTI), practical AI and digital study support each serve a distinct purpose.
Our proprietary clinical trial management system brings study documents, monitoring visit scheduling and reporting into a connected operational view.
CTMS integrations with Medrio, Veeva and Zelta connect study data to the management picture.
Investigator experience, enrollment history, study burden, staffing and capacity inform AI-assisted site assessment and study-specific recommendations.
Explore Real Time IntelligencePassword-protected, sponsor-branded portals bring documents, training and communications together. InFocus manages development and ongoing updates.
Study newsletters, enrollment updates and focused training tips support the exchange of information across your site network.
Participant payment and reimbursement tools help simplify administration for sites and sponsors.
Building on working capabilities. Extending their reach.
Our development priorities connect AI more closely to document intake and site support. These initiatives are in development, distinct from the validated workflows already in use.
From the study inbox to a review-ready record.
The next step for AI Validation: an agent that retrieves files from a study mailbox and stores them in the eTMF. An in-house CRA would confirm the AI evaluation and correct filing location.
The goal: Make document intake more efficient while retaining human quality control.
From connected study data to focused site support.
Building on existing EDC integrations, a planned AI agent would examine patterns across site data to surface potential workflow issues, critical findings and opportunities for intervention.
The goal: Give clinical teams a more informed basis for deciding where and how to support a site.
Let’s explore the technology and AI workflows that fit your program.