AI Metrics

Birmingham, AL, US All United States companies → — Founded 2019

Imaging AI Specialist

Oncology Radiology

Oncology AI Radiology & Imaging AI

Seed — $5.06M

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Products

AI Metrics

Oncology AI

AI Metrics offers AI-enabled radiology software that streamlines cancer patient evaluation, providing faster, more accurate medical imaging analysis and automated reporting for radiologists and oncologists.

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About AI Metrics

AI Metrics is a healthcare AI company specializing in advanced imaging software designed to enhance the efficiency and accuracy of radiology in cancer imaging. Their platform provides AI-powered tools for critical tasks such as tumor contouring, automatic anatomical labeling, and seamless access to prior studies. This technology empowers radiologists and oncologists to more efficiently evaluate treatment responses and streamline clinical trial assessments.

The company’s solutions aim to significantly reduce cancer read times and minimize major diagnostic errors, thereby addressing radiologist burnout and improving overall productivity within healthcare settings. By offering simplified, user-friendly workflows and automated reporting, AI Metrics helps to improve the speed, accuracy, and consistency of image analysis, ultimately supporting better patient care decisions.

Focus Areas

Medical imaging augmented intelligence radiology cancer diagnostics tumor tracking liver disease staging workflow efficiency radiologist burnout reduction automated reporting

Business Intelligence

Key Investors	Alabama Capital Network, US National Science Foundation, 701 Fund
Partnerships	Imaging Biometrics (LSN software distribution), Innolitics (software development)
Technology	AI-assisted workflows, augmented intelligence for image analysis, AI-powered tools for tumor contouring, automatic anatomical labeling, and access to prior studies.
FDA Clearances	2 cleared products (estimated)

What Physicians Need to Know

Medical Imaging & Augmented Intelligence

AI Metrics leverages augmented intelligence to enhance medical imaging analysis, particularly for advanced cancer imaging. Their AI guidance acts as an 'extra set of eyes' for radiologists, improving both accuracy and efficiency in reads.

Radiology & Cancer Diagnostics

The company specializes in revolutionizing cancer patient evaluation by significantly reducing the time required for complex cancer reads, often cutting read times in half. They focus on improving the accuracy and consistency of cancer diagnoses.

Tumor Tracking

AI Metrics provides single-click algorithms that automate tumor identification, measurement, and anatomical labeling, streamlining the process of tracking tumor progression and response to treatment.

Liver Disease Staging

They offer FDA 510(k) cleared Liver Surface Nodularity (LSN) virtual liver biopsy software. This technology assists physicians in staging chronic liver disease by analyzing nodules along the liver's surface on CT images, providing a non-invasive assessment.

Workflow Efficiency & Radiologist Burnout Reduction

AI Metrics addresses radiologist burnout by simplifying tedious and inefficient workflows associated with cancer reads. Their intuitive, easy-to-use workflows reduce stress and effort, allowing radiologists to complete tasks faster and improve load balancing.

Automated Reporting

The platform seamlessly and automatically generates clear, visualized patient reports while the radiologist conducts the study. These reports are highly preferred by oncologists over standard text-based options, enhancing communication and understanding.

Physician Tip

For physicians, AI Metrics offers a powerful tool to significantly reduce workload and combat burnout by automating repetitive and time-consuming tasks in cancer imaging and reporting. Leveraging their AI-guided workflows can lead to faster, more accurate diagnoses, improving diagnostic confidence and consistency. The clear, visualized reports can enhance communication with oncologists and patients, leading to more informed treatment decisions. Consider how integrating this solution can free up valuable time for more complex cases and direct patient interaction, ultimately improving overall patient care and radiologist well-being. Ensure proper training and seamless integration into existing PACS/RIS systems to maximize benefits.

Effective integration with existing Picture Archiving and Communication Systems (PACS), Radiology Information Systems (RIS), and Electronic Health Records (EHR) is crucial to realize the full benefits of AI Metrics' solutions. Seamless integration ensures smooth data flow, minimizes workflow disruptions, and maximizes the efficiency gains for radiologists and the broader clinical team.

At a glance

Founded 2019

HQ Birmingham, AL, US · United States

Team size 13

CEO Bob Jacobus

Funding Seed — $5.06M

FDA clearances 2 (estimated)

Products 1

Products by AI Metrics

1 product in the directory

AI Metrics

Oncology AI

Contact for pricing

What the Web Says

AI Metrics appears to be a company focused on AI-powered solutions for medical imaging analysis, particularly in oncology. Reviews suggest a strong product for automating measurements and tracking tumor progression, which is highly valued by users in healthcare. Employer reviews are less prevalent but indicate a positive work environment.

Overall: Positive

Strengths

Automates tumor measurements and tracking, saving time for radiologists and oncologists.
Improves accuracy and consistency in lesion measurement.
Integrates well with existing PACS systems.
User-friendly interface for medical professionals.
Provides valuable data for clinical trials and research.
Responsive customer support.

Limitations

Initial setup and integration can be complex for some organizations.
Steep learning curve for some advanced features.
Cost may be a barrier for smaller practices or hospitals.
Limited information available on employer reviews across major platforms.
Specific details on pricing are not readily transparent.
Some users desire more customization options for reporting.

Based on reviews from: G2, Glassdoor, Capterra, Healthcare IT News, Reddit

Last updated: 2026-07-17

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Press & Coverage

Radiology - RSNA Journals

Metrics for Artificial Intelligence in Medicine: A Reference Resource

This article presents a comprehensive, machine-interpretable framework to formalize the nomenclature and descriptions of 207 graphical, matrix, and scalar metrics used to measure AI model performance in clinical medicine. The taxonomy, part of the Radiology Ontology of AI Datasets, Models and Projects (ROADMAP), aims to standardize evaluation for reproducibility and adoption.

2026-03

HealthManagement.org

AI Metrics Taxonomy Aims to Standardise Medical Evaluation

A 2026 special report in Radiology: Artificial Intelligence introduced a machine-interpretable taxonomy of performance metrics within the ROADMAP framework to standardize medical AI evaluation. This framework provides a shared vocabulary for comparing AI systems, checking reporting completeness, and detecting issues like bias.

2026-06

unknown

AI Monitoring: From Model Metrics to Patient Outcomes

This article discusses the importance of monitoring AI performance in healthcare, emphasizing that health systems should require monitoring at a defined cadence, specify metrics, and establish thresholds for re-evaluation. It highlights the need to move beyond statistical performance to also measure outcome performance and user adoption.

2026-03

PitchBook

AI Metrics 2026 Company Profile: Valuation, Funding & Investors

AI Metrics was founded in 2019 and is headquartered in Birmingham, AL, with 13 employees. The company has raised $5.06M in funding, including a $952K later-stage VC deal on November 26, 2025, and grants in 2020 and 2021.

2025-11

medRxiv

On evaluation metrics for medical applications of artificial intelligence

This article provides a guide to understanding and interpreting different evaluation metrics for machine learning models in gastroenterology, using examples from peer-reviewed studies. It also offers an open-source web-based tool to aid in calculating relevant metrics for researchers and clinicians.

2021-04

EliseAI

Measuring AI Impact in Healthcare: Metrics That Drive Decisions

This article addresses the challenge for healthcare practice managers in evaluating AI tools for operational efficiency and patient outcomes due to fragmented healthcare data. EliseAI designed a metrics dashboard to integrate internal data with EMR systems, providing real-time insights into actionable outcomes like scheduling and call handling.

2025-11

unknown

U.S. Regulators Press Companies to Reveal AI Use u2014 What Investors Need to Know

U.S. regulators are increasing pressure on public companies to disclose their use of AI, particularly systems affecting financial results, consumer outcomes, or governance. This push from securities and consumer protection agencies aims to adapt existing disclosure frameworks to cover AI models, datasets, and their potential failures.

2026-07

Equilar

AI as a Performance Metric: What Companies Are Disclosing Now

Companies are increasingly incorporating AI-focused performance objectives into executive compensation programs, particularly within annual incentive plans. Examples include Qorvo's long-term incentive plan with an AI tool deployment objective and Juniper Networks' strategic goal to capitalize on AI opportunities.

2026-03

Frequently Asked Questions

What specific medical imaging solutions does AI Metrics offer, particularly for cancer and liver disease diagnostics?

AI Metrics provides an advanced cancer analysis system designed to improve the efficiency and accuracy of cancer reads, helping radiologists evaluate patients twice as fast. Additionally, their Liver Surface Nodularity (LSN) software offers a non-invasive method for detecting and staging liver fibrosis and decompensation using standard CT scans, reducing the need for invasive biopsies or specialized MRI equipment.

How does AI Metrics' augmented intelligence improve radiologist workflow efficiency and help reduce burnout?

AI Metrics' augmented intelligence streamlines radiology workflows by reducing the average read time for cancer patients significantly, from approximately 18.7 minutes to 9.8 minutes. This efficiency, combined with guided workflows and automatic tracking of incidental findings, alleviates the burden of complex tasks and contributes to reducing radiologist burnout by allowing them to focus more on image interpretation.

What are the key features and benefits of AI Metrics' automated reporting for physicians and administrators?

AI Metrics automatically generates clear, visualized patient reports in the background while radiologists conduct studies, which are preferred by oncologists over standard text-based options. These reports automatically include graphs, tables, images, and text, enhancing communication and reducing the potential for human error in documentation.

What is AI Metrics' regulatory compliance status for its medical imaging AI solutions?

As of early 2020, AI Metrics was actively pursuing CE Mark and U.S. Food and Drug Administration (FDA) 510(k) clearance for its virtual liver biopsy software with the assistance of its partner, Imaging Biometrics. Generally, AI-enabled medical devices in the U.S. must adhere to FDA guidelines for design, documentation, and monitoring, while in Europe, they must comply with MDR/IVDR and the EU AI Act.

How is AI Metrics' pricing structured, and what factors influence the cost for healthcare organizations?

While specific pricing details for AI Metrics are not publicly disclosed, healthcare AI pricing models often incorporate outcome-based metrics, where organizations pay based on achieved clinical or operational improvements. Pricing can also be volume-based, such as per-record or per-study, potentially including fixed fees and additional tiers for regulatory compliance features.

What kind of support and implementation assistance does AI Metrics provide to ensure successful integration into clinical practice?

Successful AI implementation requires seamless integration and user acceptance, with effective support often including comprehensive training, change management, and alignment with existing clinical workflows. AI Metrics aims to provide intuitive, easy-to-use workflows that act as a supportive 'teammate' rather than an additional burden, suggesting a focus on practical integration and user experience.

Does AI Metrics have partnerships that enhance its offerings or expand its reach in the healthcare market?

Yes, AI Metrics has established partnerships, notably with Imaging Biometrics, which serves as a global distribution partner for its virtual liver biopsy software. Such collaborations are crucial for AI startups to accelerate adoption and integrate solutions into broader healthcare systems.

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