SigTuple AS76 digital morphology analyser launched

SigTuple has launched the SigTuple AS76 digital morphology analyser, an AI-enabled system designed to automate peripheral blood smear microscopic review. The system combines automated digital microscopy with edge AI computing to deliver faster and more consistent results while keeping data processing local.

The analyser is powered by NVIDIA RTX and performs high-throughput image analysis directly on the device. This architecture allows near-instant results, even for large sample batches, without relying on internet connectivity.

Automated review of peripheral blood smears

The AS76 system can load up to six peripheral blood smear slides simultaneously. It scans each slide in diagnostic detail and generates an AI-assisted report for expert validation.

Key automated functions include:

• Generation of a 200-cell leukocyte differential

• Red blood cell morphology analysis

• Platelet morphology flagging, including detection of aggregates

All AI inference and image processing are performed locally on the device.

The analyser is equipped with 20×, 40× and 100× objectives mounted on an automated turret. While it launches with peripheral blood smear capabilities, the platform is designed for future software upgrades to support tissues, fluids, bone marrow and microbiology slides.

This positions the system as a potential digital replacement for traditional analog microscopes in laboratories.

Edge AI and data privacy focus

A defining feature of the SigTuple AS76 digital morphology analyser is its on-device AI architecture. By running all processing locally, the system eliminates latency and reduces dependency on network infrastructure.

The local inference model ensures patient data remains within the laboratory environment. This approach addresses concerns around data privacy and connectivity limitations in diagnostic settings.

Tathagato Rai Dastidar, Founder and CEO of SigTuple, stated that edge AI enables intelligence to remain where data is generated, supporting rapid analysis while maintaining confidentiality. He noted that the system aims to improve both speed and consistency in laboratory workflows.

Standardisation and workload reduction

By applying AI-driven cell pre-classification, the AS76 standardises smear review at scale. The system surfaces atypical findings quickly for expert confirmation.

The automation of manual review tasks is designed to reduce laboratory workload and shorten turnaround time.

The analyser is CE-marked under IVDR, indicating compliance with European safety and performance requirements.

Built on existing AI microscopy deployments

SigTuple’s AI-powered microscopy solutions have previously been deployed in regions with limited access to specialist expertise. In remote and underserved areas, digital microscopy has enabled centralised pathologist review and earlier detection of serious conditions.

The AS76 builds on these deployments by combining high-resolution imaging with embedded edge AI computing.

Tobias Halloran, Director of EMEAI Startups and Venture Capital at NVIDIA, stated that India’s AI startup ecosystem is advancing rapidly and highlighted NVIDIA’s support programmes that provide accelerated computing access and infrastructure to startups.

Implications for diagnostic laboratories

The SigTuple AS76 digital morphology analyser reflects a shift toward integrated AI systems that operate within laboratory environments rather than through cloud-dependent models.

With automated classification, local inference and multi-application readiness, the platform is positioned to support scalable, standardised diagnostic workflows while maintaining data control within the lab.

For laboratories managing increasing workloads and compliance demands, edge-enabled digital microscopy presents a structural change in how routine smear reviews are conducted.

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