Amplifying Human Intelligence in the Lab
Clinlab.AI is the first AI co-pilot built for clinical labs — amplifying the capabilities of every scientist and manager. Our agentic AI platform continuously forecasts demand, monitors quality in real time, and prevents errors before they reach patients. The result: faster turnaround, fewer compliance issues, and millions saved for healthcare entities.
70% of Clinical Decisions Rely on Lab Results, Yet Labs Still Operate Without AI’s Advantage
Delays in results, repeated quality failures, and costly re-testing all drive up patient length of stay and increase operational waste. Manual QC checks and outdated spreadsheets can’t keep pace with today’s demands — leading to compliance gaps, higher lab costs, and unnecessary readmissions. The future of diagnostics requires more than human throughput. It requires intelligence that anticipates problems before they impact patients and budgets.
One Platform. Three Powerful AI Co-Pilots.
Across 200+ labs and 300K+ monthly tests, Clinlab.AI has proven that labs don’t need more people to solve today’s challenges — they need smarter tools. Our AI platform augments every layer of the lab with three specialized co-pilots designed to amplify, not replace, the work of scientists and managers.
Together, these AI co-pilots provide continuous foresight across operations. They forecast volumes and staffing needs, safeguard quality in real time, and detect health trends before they escalate. By turning raw analyzer data into guided action, Clinlab.AI enables labs to run faster, safer, and more predictively — delivering results you can trust while reducing costly delays and compliance risk.
Stanley: Manager-Assist
Your lab’s operations co-pilot. Predicts daily test volumes, optimizes staffing and schedules, and prevents reagent waste or stockouts — ensuring resources are ready when and where they’re needed.
Marie: Scientist-Assist
Your lab’s quality co-pilot. Real-time QC monitoring with Westgard & Six Sigma logic, plus real-time patient QC (RTPQC). The right issues are flagged before patients are affected.
Elara: Patient-Assist
Your lab’s population co-pilot. Detects subtle health shifts, predicts disease transitions before escalation, and enables earlier intervention — improving outcomes across entire patient populations.
Proven in the Field, Not Just Theory
Nationwide Vitamin D Recall
In April 2024, Clinlab.AI's Marie flagged irregularities in low-end sample recoveries during testing of a large diagnostic company’s Vitamin D Assay calibrator. While traditional release testing had verified the calibrator within specifications, Clinlab.AI's proprietary algorithms detected subtle inconsistencies that could impact low-range diagnostic accuracy. This early detection underscored the powerful role of AI in identifying quality control gaps that may not be immediately evident through conventional testing processes.
IT Failure: Analyzer Drift
A missed calibration on a CBC analyzer caused hemoglobin values to steadily drift upward, producing inaccurate results that could have gone unnoticed for days. Traditional monitoring offered no immediate warning, leaving patients at risk and creating the potential for widespread retesting. Marie detected the deviation early, identifying the drift before results were released, and enabling rapid troubleshooting. By restoring accuracy without disrupting care, Marie not only prevented compromised outcomes but also protected the lab from costly delays and compliance scrutiny.
QC Setup Failures
Manual QC processes missed critical errors across multiple points of setup. Inactive QC lots were never activated after testing, incorrect SD values went undetected for weeks, and wrong QC transmissions created compliance exposure. Each of these issues risked compromised results and regulatory violations that would have gone unnoticed under conventional oversight. Marie surfaced the failures instantly in real time, flagging the violations and preventing costly errors before they could impact patient care or compliance audits.
Pre-Analytical Error: Mislabeled Sample
A mislabeled PSA sample introduced the risk of reporting incorrect results to a patient. In a manual process, such pre-analytical errors are difficult to detect and often remain hidden until after results are delivered, creating potential harm and reputational risk. Elara identified the inconsistency instantly, flagging the mismatch before results left the lab. By catching the problem at its source, Elara prevented misdiagnosis, reduced unnecessary repeat testing, and underscored the value of AI in safeguarding patients where manual systems frequently fall short.