A digital morphology analyzer is an automated instrument that combines robotic slide handling, AI microscopy and deep learning classification to perform detailed cellular morphology analysis — replacing manual microscopic review with intelligent, consistent automation. SigTuple's AI100 is a next-generation digital morphology analyzer that digitises peripheral blood smears and urine sediment at 40× resolution, enabling smear review automation across WBC differential, RBC morphology and platelet morphology assessment. Unlike traditional cell counters, a digital morphology analyzer captures full visual evidence for every cell — supporting AI morphology analysis, remote pathologist sign-off and complete elimination of inter-observer variability from the diagnostic process.

Smear review automation uses robotics to digitise a stained & prepared glass slide, then applies trained AI morphology analysis algorithms to identify and classify every cell in the monolayer. SigTuple's Shonit™ application delivers end-to-end smear review automation for peripheral blood smears — generating a full WBC differential automation output, RBC morphology grading to ICSH standards, and platelet analysis with visual evidence. The pathologist receives a pre-classified, structured report and can validate or override individual cells with a single click — combining the efficiency of automation with the precision of expert oversight.

Peripheral blood smear (PBS) analysis is the microscopic examination of a stained blood film to assess white blood cell morphology, red blood cell shape, size and colour, and platelet morphology and count estimation. It is the cornerstone of haematology workflows for detecting conditions including anaemia, leukaemia, infections and morphological abnormalities. SigTuple's AI100 automates PBS analysis through AI microscopy — digitising slides, applying AI morphology analysis algorithms, and producing ICSH-graded reports with full visual evidence. As a digital morphology analyzer, AI100 delivers smear review automation that is faster, more consistent and fully auditable.

AI morphology analysis applies deep learning models to high-resolution digital images of stained blood smears or urine sediment, pre-classifying each cell and flagging morphological abnormalities automatically. In digital pathology workflows, AI morphology analysis dramatically reduces the time pathologists spend on routine differential counting — freeing them to focus on complex or flagged cases. SigTuple's AI models are trained on millions of annotated cells and are capable of detecting subtle features — atypical lymphocytes, blast cells, hemoparasites and toxic granulations — that may be missed under time-pressured manual review. This level of AI morphology analysis is embedded in every scan processed by the AI100 platform.

Yes. WBC differential automation through AI significantly improves consistency, throughput and turnaround time in haematology workflows. SigTuple's Shonit™ performs WBC differential automation by pre-classifying white blood cells — delivering a 7-part differential with atypical cells, Immature granulocytes, and nRBCs. As part of a digital morphology analyzer workflow, WBC differential automation eliminates inter-observer variability, reduces analyst fatigue and enables high-volume processing without compromising quality. Pathologists review the AI-generated differential and apply their expertise only where clinical judgement adds value.

AI100 integrates into existing hematology workflows via bi-directional LIS integration, allowing seamless data exchange with laboratory information management systems. WBC differential automation results, RBC morphology flags and urine sediment findings are automatically transmitted to the LIS — eliminating manual data entry and reducing transcription errors. The browser-based remote pathology review interface enables pathologists to access cases from any device, while cloud storage ensures all scan data is retained indefinitely. AI100's smear review automation capabilities fit directly into existing laboratory processes with minimal workflow disruption.

Yes. AI100 is purpose-built for remote pathology review. Once AI smear review analysis is complete, the full case — all cell images, and AI morphology analysis classifications — is accessible via a secure, browser-based digital pathology interface from any location. Remote pathology review enables centralised specialist oversight across multiple laboratory sites, multi-expert consultation on complex morphology cases, and pathologist sign-off without physical presence in the laboratory. For diagnostic networks seeking to centralise their digital pathology review operations, AI100's remote pathology review capability is one of the core operational advantages.

AI100 is designed for small and medium clinical laboratories seeking to introduce AI microscopy, smear review automation and digital morphology analyzer capability without large capital investment. It suits hospital laboratories, standalone diagnostic centres and reference laboratory networks requiring FDA 510(k)-cleared, CE IVDR-compliant digital pathology capability for both peripheral blood smear analysis (Shonit™) and urine sediment analysis (Shrava™). AI100's WBC differential automation, AI morphology analysis, cloud-based architecture and browser-based remote pathology review interface make it accessible to laboratories of any size modernising their hematology and urinalysis workflows.