Scopea.
Turn pixels into evidence.
Computer vision for microscopy, gels, blots, histology, plate reads, and instrument streams—producing structured measurements with confidence, provenance, and quality control.
Scientific images should not remain trapped as subjective pixels.
A large share of bench analysis still depends on manually reading microscopy, gels, blots, histology, and instrument outputs. The work is slow, variable between scientists, and difficult to reproduce.
Scopea applies modality-specific vision models to quantify images, detect quality issues, attach confidence, and emit structured results directly into Sciento's reasoning, validation, and reporting workflows.
Perception designed for scientific modalities.
Segmentation
Identify cells, tissues, colonies, bands, lanes, and regions of interest.
Quantification
Convert visual observations into reproducible, queryable measurements.
Automated QC
Flag artifacts, saturation, loading-control failures, anomalies, and low confidence.
Multimodal fusion
Interpret image evidence alongside assay metadata and instrument context.
Audited outputs
Preserve source image, model version, confidence, transformations, and overrides.
Edge runtime
Run low-latency perception close to instruments for future closed-loop acquisition.
From acquisition to structured result.
Capture the source
Receive images, frames, instrument data, and assay metadata.
Apply the modality model
Segment, detect, classify, and quantify the relevant structures.
Assess quality
Score confidence and surface artifacts or ambiguous measurements.
Publish the result
Send audited measurements to analysis, Verita, and reporting.
Cloud training with an instrument-edge path.
Observation that closes the experimental loop.
Make instrument output reproducible by default.
Choose one imaging workflow and turn its raw pixels into trusted, structured evidence.