Just Do Science!
Most wet-lab workflows still separate protocol execution from data capture. CCA connects instruments and software so protocol state, measurements, and environmental context stay in one record, making experiments easier to reproduce and compare.
Fragmented Data, Limited Insight
Modern biology generates more data than ever, but legacy infrastructure creates barriers at every step.
- Data dispersed across proprietary software and spreadsheets
- Multi-step experiments are difficult to automate consistently
- Reproducibility and traceability limited
- Scaling increases burden rather than insight
Integrated Experiment Infrastructure
CCA links telemetry, imaging, and execution logs so measurements can inform defined protocol actions. Runs stay traceable, comparable, and ready for downstream analysis.
Experiment-first workflow
- Run experiments via UI
- View data on interactive graphs
- Track samples & inventory
- Schedule instrument time
Analysis-focused workflow
- Explore experiment data
- Run statistical analysis
- Design experiments (DoE)
- Decision support from quantitative trends
Compute-heavy workflow
- Access data via API
- Build virtual cell models
- Run ML pipelines
- Bulk image processing
CCA Labs
Unified Platform for Cell Culture Automation
UI
Protocols
Experiments
Samples
Inventory
Scheduling
Analytics
DoE
ML Pipeline
API
CCA Instruments • Deep Integration
Environmental telemetry
Automated imaging
Research automation
Manufacturing scale
Third-Party Instruments • Standard Integration
How CCA Products Compare
Compare capabilities across the CCA product portfolio, from monitoring and imaging through automated R&D and scale-up execution.
Capability
Pebble
CCA Microscope
DALI-24
DALI-500
CCA Labs Integration
Lab Management & Lab in the Loop Orchestration
Structured Data & Audit Trail
Protocol-linked data and metadata for traceability and reproducibility
Remote Monitoring & Alerts
Telemetry alerts with configurable thresholds and rules
REST API
Open APIs for orchestration and data export
Environmental Monitoring
Temperature, CO₂, O₂, and humidity telemetry with time-aligned context
Environmental Control
Active control of temperature, CO₂, O₂ (Hypoxia)
Full Plate Imaging
Morphology, Confluency, Viability, with Brightfield and Fluorescence
SBS Plate Throughput
Scalable from single-plate to high-throughput workflows
Automated Liquid Handling
Automated seeding, feeding, passaging, and harvest with protocol-defined rules
Plate Transfer
Automated plate transfer between integrated modules
Experimental Maturity
Progression from monitoring to controlled imaging to closed-loop automation at scale
2026–2029 Roadmap
Pebble – Telemetry System
Continuous environmental telemetry for temperature, humidity, CO₂, and O₂, linked to protocol steps and experiment timelines.
CCA Labs – Platform Launch
Protocol and experiment orchestration layer that keeps samples, instrument outputs, and metadata in one protocol-linked record.
CCA Microscope – Integrated Incubator
Automated imaging with time-aligned environmental context, enabling longitudinal cell-state analysis with traceable acquisition metadata.
dALI 24 – Modular Closed System
Research-scale closed-loop automation combining imaging, incubation, and liquid handling for protocol-defined seeding, feeding, passaging, and harvest.
dALI 500 – Manufacturing Scale System
Manufacturing-scale extension of the dALI workflow model, preserving protocol logic and data structure while increasing throughput to 500+ plates.
Automation for Your Cell Culture
Monitor, detect, recommend, then execute: CCA workflows are designed to move through these stages with explicit rules, measurements, and traceable outcomes.
Routine Culture Operations
iPSC & Pluripotent Stem Cells
iPSC maintenance is time-sensitive and variable when decisions rely on subjective manual checks. CCA provides automated whole-plate imaging with quantitative confluency and morphology tracking, forecasting when colonies reach defined thresholds so feeding and passaging occur on time, operator-guided or fully automated with dALI.
Differentiation Protocols
Multi-day differentiation runs depend on precise timing and consistent execution, where missed transition windows can shift outcomes. Checkpoint imaging documents stage progression across the plate, and deviation alerts flag drift early, helping align media changes and factor additions to culture state before critical stage transitions close.
Primary & Adult Stem Cells
Primary and adult stem cell cultures face donor variability and limited expansion, making failed runs costly. CCA provides plate-wide morphology and confluency checkpoints to detect early stress or drift, adjust feeding timing, and keep traceable records across donors, operator-guided or automated with dALI.
Organoid Research & 3D Tissues
Organoid development is dynamic and context-dependent. Longitudinal imaging tracks growth and morphology over days, while time-aligned logs of temperature, CO₂, and O₂ provide environmental context to interpret phenotypes and support controlled hypoxia workflows across plates and runs.
Tumour & Hypoxia Studies
Tumor and hypoxia assays are highly sensitive to microenvironment, where small O₂ shifts can change phenotype and drug response. Environmental controls are critical: Pebble tracks O₂ and CO₂ continuously, and CCA links each image to the recorded environment at capture time for traceable, reproducible longitudinal analysis.
Standard Cell Lines
Routine maintenance of standard cell lines is time-intensive and prone to gradual drift. Daily imaging QC enables early detection of morphological changes and growth deviations, while dALI automates feeding and passaging with protocol-linked, traceable records to support consistent maintenance across plates and users.
The Right Approach
We design instruments and software as one coordinated system so protocol state, measurements, and context stay synchronized from experiment start to analysis.
Instrument-Software Co-Design
Measurement, control, and data capture are designed together so critical context is not lost between instrument and software layers.
Structured Capture
Data is captured at acquisition time with protocol and timestamp context, rather than reconstructed later from notes and exports.
Observable & Reproducible
Each run produces a reviewable record linking inputs, actions, measurements, and deviations, improving comparability across repeats.
Scalable Platform
Protocol definitions and data structure are preserved from bench workflows to higher-throughput execution.
From Bench to Scale, Same Platform
Start with one workflow and keep your data model consistent as you scale. The same protocol-linked record supports day-to-day decisions, QA review, and long-horizon process development.