Custom AI Image Analysis, Built on Your Data

When off-the-shelf tools can’t handle your assay, we build, train, and deploy a model that does. Trained on your images. Validated against your standards. Delivered into a workflow your team can actually use.

The problem

Why generic AI tools fall short

Most cell biology assays don’t fit a pre-trained model. Hiring an internal team isn’t realistic for most labs. There’s a third option.

SnapCyte

How it Works

From problem to working model

Scope

Send sample images and describe what you want to measure. We assess feasibility and define success metrics. No charge.

Week 1

Data & annotation

We assess your dataset, fill gaps, and handle expert annotation. Our annotators are scientists, not contractors.

Week 2-8

Train & validate

We train iteratively against agreed accuracy targets. You see performance on your data at every checkpoint.

Week 4-10

Deploy your way

Hosted on SnapCyte, integrated into your pipeline via API, or fully handed off , we deploy however fits your team and existing workflows.

Week 10+

Cost Effective

The Same Outcome. A Fraction of the Cost.

The typical cost of assembling an internal AI team  exceeds $600,000+ per year in salaries alone, not including benefits, infrastructure, and training time.

With SnapCyte, you get access to a complete AI engineering team at a fraction (20-40%) of the cost, with no long-term commitments and faster time to results.

Case study

How Zymeworks Automated Spheroid Segmentation and Viability Readouts for their ADC team with SnapCyte in 10 weeks.

Why SnapCyte?

Scientists who do AI, not the other way around

Built by scientists

Biologists and ML engineers in the same room. Fewer translation errors, faster iteration on what matters scientifically.

Messy data is fine

Variable staining, inconsistent imaging, partial datasets, that’s what we train on, because that’s what your team generates.

Flexible deployment

SnapCyte platform, API integration, or full handoff. We integrate where your team works.

Transparent proces

You see model performance at every checkpoint, not just at delivery. No black boxes.

Fast to first results

Most projects deliver usable results in 6–8 weeks. Not quarters.

Scoping is free

Send us sample images. We’ll assess feasibility and scope the project at no charge.

Have a dataset and an imaging problem?

Send us sample images. We'll tell you within a week whether AI can solve it , at no charge.

Frequently asked questions

Find your answers here or contact us

Our process begins with scoping to understand your research needs and  challenges. We then design and train AI models using curated datasets tailored to your requirements, ensuring precision and relevance to your workflows.

We use MLOps-driven infrastructure to organize and manage your data pipelines. This includes versioning, feedback loops, and scalability to ensure your AI models remain reproducible and adaptable as your research evolves.

Timelines vary depending on the complexity of your project. However, our agile approach allows us to deliver initial results quickly, typically within weeks, while continuing to refine models based on your feedback.

We provide ongoing support to ensure seamless integration into your workflows. This includes user training, regular updates, and optional enhancements to your AI models as your research progresses

Absolutely. Our team of experts collaborates with you to assess your challenges and recommend solutions that best fit your microscopy data and research needs.

Not necessarily. Our solutions are designed to integrate with your setup and workflow. We can provide recommendations if needed to optimize your imaging  workflows or systems.

resources

Latest insight and updates

Adherent Cell Count: More Than Just a Number

Cell Counting in Cell Culture: How to Reduce Variability

How Zymeworks Automated Spheroid Segmentation and Viability Readouts with SnapCyte