Shukun

About Shukun

Shukun provides AI‑powered digital doctor agents that automatically analyze multimodal medical imaging and clinical data across major organ systems, delivering quantitative assessments, risk scores, and treatment recommendations. The platform leverages a large multimodal medical model, cloud‑based inference pipelines, and FHIR‑compatible APIs to integrate with hospital information systems, offering rapid, consistent diagnostics for hospitals, imaging centers, and health‑screening organizations.

<problem>Healthcare providers often face limited access to advanced diagnostic imaging analysis and require extensive specialist time to interpret multi‑modal medical data, leading to delays and variability in patient care.</problem> <solution>Shukun delivers a suite of AI‑powered “digital doctor” agents that analyze imaging and clinical data across major organ systems—including heart, brain, chest, abdomen, breast, thyroid and musculoskeletal regions. Built on a multimodal medical large model (“ShukunKun”), the platform integrates cloud computing, big data, AI algorithms, IoT connectivity, and AR‑enabled visualization to generate quantitative assessments, risk scores, and treatment recommendations. Results are delivered through secure web dashboards and can be integrated with hospital information systems, enabling clinicians to obtain rapid, consistent insights without extensive manual review.</solution> <features> - Multimodal AI models for over 100 disease indications covering cardiovascular, neurovascular, pulmonary, hepatic, breast, thyroid and orthopedic imaging. - Automatic extraction of quantitative biomarkers (e.g., plaque analysis, calcium scoring, bone age, lesion segmentation) with built‑in validation and regulatory certifications (NMPA, FDA, EU MDR). - Cloud‑hosted inference pipeline that scales to high‑volume hospital and screening center workloads while ensuring data encryption and patient privacy. - Web‑based reporting interface with visual heat‑maps, trend graphs, and customizable alerts for clinicians. - Standardized APIs (FHIR‑compatible) for seamless integration with PACS, EMR/EHR, and tele‑medicine platforms. - Support for on‑premise deployment of the large model in hospital data centers for latency‑critical or data‑sovereignty requirements. </features> <target_audience>Primary customers are hospitals, medical imaging centers, and large‑scale health‑screening organizations seeking AI‑assisted diagnostic support across multiple specialties.</target_audience>

What does Shukun do?

Shukun provides AI‑powered digital doctor agents that automatically analyze multimodal medical imaging and clinical data across major organ systems, delivering quantitative assessments, risk scores, and treatment recommendations. The platform leverages a large multimodal medical model, cloud‑based inference pipelines, and FHIR‑compatible APIs to integrate with hospital information systems, offering rapid, consistent diagnostics for hospitals, imaging centers, and health‑screening organizations.

Where is Shukun located?

Shukun is based in Beijing, China.

When was Shukun founded?

Shukun was founded in 2017.

How much funding has Shukun raised?

Shukun has raised $105.8M.

Location
Beijing, China
Founded
2017
Funding
$105.8M
Employees
72 employees
Investors
5Y CapitalBhzs CapitalJy CapitalParagonvcZbqlct
S

Shukun

Inactive

Shukun provides AI‑powered digital doctor agents that automatically analyze multimodal medical imaging and clinical data across major organ systems, delivering quantitative assessments, risk scores, and treatment recommendations. The platform leverages a large multimodal medical model, cloud‑based inference pipelines, and FHIR‑compatible APIs to integrate with hospital information systems, offering rapid, consistent diagnostics for hospitals, imaging centers, and health‑screening organizations.

Beijing, ChinaFounded 201772300+ followers10/10 TractionRelative Traction Score based on online presence metrics compared to companies in the same age group.
Updated 2 months ago

Funding

$105.8M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.

GSPC
Funding rounds are not available yet.

Founders

Product

Problem

Healthcare providers often face limited access to advanced diagnostic imaging analysis and require extensive specialist time to interpret multi‑modal medical data, leading to delays and variability in patient care.

Solution

Shukun delivers a suite of AI‑powered “digital doctor” agents that analyze imaging and clinical data across major organ systems—including heart, brain, chest, abdomen, breast, thyroid and musculoskeletal regions. Built on a multimodal medical large model (“ShukunKun”), the platform integrates cloud computing, big data, AI algorithms, IoT connectivity, and AR‑enabled visualization to generate quantitative assessments, risk scores, and treatment recommendations. Results are delivered through secure web dashboards and can be integrated with hospital information systems, enabling clinicians to obtain rapid, consistent insights without extensive manual review.

Target Audience

Primary customers are hospitals, medical imaging centers, and large‑scale health‑screening organizations seeking AI‑assisted diagnostic support across multiple specialties.

Features

  • Multimodal AI models for over 100 disease indications covering cardiovascular, neurovascular, pulmonary, hepatic, breast, thyroid and orthopedic imaging.
  • Automatic extraction of quantitative biomarkers (e.g., plaque analysis, calcium scoring, bone age, lesion segmentation) with built‑in validation and regulatory certifications (NMPA, FDA, EU MDR).
  • Cloud‑hosted inference pipeline that scales to high‑volume hospital and screening center workloads while ensuring data encryption and patient privacy.
  • Web‑based reporting interface with visual heat‑maps, trend graphs, and customizable alerts for clinicians.
  • Standardized APIs (FHIR‑compatible) for seamless integration with PACS, EMR/EHR, and tele‑medicine platforms.
  • Support for on‑premise deployment of the large model in hospital data centers for latency‑critical or data‑sovereignty requirements.
1
This profile is AI-generated and may contain inaccuracies.