Automata x CellVoyant: Autonomous Workflows for Adaptive Cell Culture

Closed-loop AI-driven cell culture system integrating CellVoyant FateView™ and FateDrive™ with Automata LINQ™

CellVoyant partnered with Automata to implement an adaptive, AI-driven cell culture workflow by integrating CellVoyant’s AI foundation models with Automata’s LINQ™ platform.

The collaboration brings together:

  • FateView™ — real-time, label-free live-cell analysis
  • FateDrive™ — in silico process optimisation
  • Automata LINQ™ — modular lab automation

Together, these components support closed-loop, AI-controlled cell culture.

The Challenge: Limitations of Traditional Cell Culture Workflows

Traditional cell-based workflows are often lengthy and complex, typically involving:

  • Daily manual intervention
  • Destructive sampling for quality metrics
  • Trial-and-error optimisation
  • Fixed automation with limited adaptability

As described in the joint case study, many legacy automation platforms are monolithic and unable to dynamically interface with AI models. As a result, they struggle to accommodate the inherent variability of biological systems.

To support adaptive control, CellVoyant required an automation platform capable of responding to real-time biological signals rather than enforcing static workflows.

The Solution: Integrating FateView™, FateDrive™, and LINQ™

To address these constraints, CellVoyant integrated its AI models with Automata’s LINQ™ platform to enable direct, real-time interaction between analysis, optimisation, and execution.

How the Integrated System Works

The integrated workflow operates as a continuous closed loop:

  • Real-time cell state extraction: Label-free live microscopy images are analysed using FateView™, which extracts quantitative cell-state information without destructive sampling.
  • AI-driven protocol optimisation: Live cell-state data is fed into FateDrive™, which evaluates culture performance and generates updated process parameters.
  • Automated execution: The optimised instructions are executed automatically through Automata’s LINQ™ platform, interfacing with liquid handling and imaging systems to apply protocol updates in real time.

Case Study: Closed-Loop Cardiomyocyte Differentiation

In a proof-of-concept study described in the January 2026 case study, the integrated system was applied to a 1–2 week cardiomyocyte differentiation protocol from human pluripotent stem cells.

Within the workflow:

  • FateView™ quantified live cell populations and predicted OCT4 expression non-destructively
  • Cell state measurements and predicted outcomes were streamed into FateDrive™
  • FateDrive™ simulated millions of protocol variations in silico
  • Updated growth factor concentrations and timing were executed automatically via LINQ™ liquid handling

Reported outcomes included:

  • Eightfold improvement in differentiation efficiency over the baseline protocol
  • 60% improvement compared to a parallel DOE-based optimisation run
  • Continuous 24/7 operation, including weekends, without manual intervention

All monitoring and optimisation were performed using non-destructive, label-free imaging throughout the workflow.

Operational Impact 

Real-time biological insight is directly linked to modular automation, enabling adaptive control during multi-day cell culture workflows.

  • Real-time analysis integrated with automated execution
  • Protocol adjustments applied during active differentiation processes
  • Reduced reliance on destructive endpoint assays
  • Continuous data generation to inform ongoing optimisation

Instead of relying on fixed automation scripts, workflows respond dynamically to live cellular behaviour.

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