UnifiedFlowInfrastructure for Evidence

Analysis workflows for neuroscience labs

From experimental data to reproducible analysis.

We build and support your lab’s analysis workflows, so you can process recordings, review results, and reuse your methods without rebuilding the pipeline every time.

Discuss your workflowExplore neuroscience workflows

From experimental data to a traceable result.

One connected record
  1. 01

    Your experimental data

    Recordings linked to acquisition settings and experimental design.

  2. 02

    Repeatable methods

    Run your analysis with a defined method and settings.

  3. 03

    Researcher judgment

    Record what you accept or exclude, and why.

  4. 04

    Connected results

    Trace a result back to the work behind it.

We help set up the workflow and support your team as the research evolves.

Neuroscience first

Built around the data you collect.

Our current software focus is calcium imaging and fiber photometry. Explore how we approach each, from preparing recordings to researcher review.

Image-based analysis

Calcium imaging

From an image sequence to reviewed regions, traces, and a connected analysis record.

Signal-based analysis

Fiber photometry

Correct and normalize recorded signals, align activity to experimental events, and review the trials included in your analysis.

From recording to result

From recordings to results
you can revisit.

Scattered scripts and review notes make an analysis hard to repeat. We bring the processing steps and scientific decisions into a record your team can work from.

01 / Define the experiment

Configure the analysis around the experiment.

Use the preparation, acquisition settings, and research question to select methods and configure the workflow.

Start with what was measured and what you want to learn.

A recording with its acquisition settings. The source recording stays linked to the experimental design and instrument settings.01 / EXPERIMENTAL DESIGNAcquisition settingsRecording AOne source, kept in view
The source recording stays linked to the experimental design and instrument settings.

02 / Process and review

Keep scientific review part of the process.

Run the selected methods with their settings recorded. Researchers inspect the outputs and document what they accept or exclude.

Your team makes the scientific decisions.

Methods and researcher review. Processing choices and review decisions belong to the same working record.02 / METHODS + JUDGMENTSelected methodVersion + run settingsResearcher reviewDecisions + reasons
Processing choices and review decisions belong to the same working record.

03 / Return to the evidence

Trace a result back to the work.

Follow an output to its recording, method version, parameters, and review decisions when you need to investigate or revisit an analysis.

Give the next researcher a clear starting point.

An output with a route back. The connected record makes the work easier to revisit, explain and hand over.03 / CONTINUITYConnected outputSource + method + reviewA result with a route backData · methods · decisions · outputs
The connected record makes the work easier to revisit, explain and hand over.
Explore the analysis approach

Refined through use

The next analysis startswith what you’ve learned.

Keep a reference for re-runs, comparisons, and model development.

Run new recordings through established methods, compare revisions, and develop data science approaches from selected review examples. Researchers evaluate changes before accepting new analysis behavior.

See what a workflow records
Acquisition records and reviewed methods support re-runs, evaluated revisions, and model developmentA retained research reference connects source data, methods, parameters and review decisions to three paths: repeat and extend analyses with linked run records; compare revised results and settings; and curate examples, derive features, train models and evaluate them. Researcher review remains part of accepting new behavior.Research data scienceRepeat analysis. Evaluate changes. Develop models.Accepted workflowA reference to return toSource dataMethods & versionsSettings & parametersReview decisionsThe reference stays intactRe-run & extendReuse the method.Keep every run traceable.RepeatExtendBatchSame methodNew run recordsCompare & refineInspect the change.Retain QC decisions.ReferenceProposed revisionData science & MLCurate review examples.Explore features.Train and evaluate.CurateFeaturesTrainEvaluateNew behavior is evaluated before acceptance.Acquisition records and reviewed methods support re-runs, evaluated revisions, and model developmentA retained research reference connects source data, methods, parameters and review decisions to three paths: repeat and extend analyses with linked run records; compare revised results and settings; and curate examples, derive features, train models and evaluate them. Researcher review remains part of accepting new behavior.Research data scienceRepeat analysis. Evaluate changes. Develop models.Accepted workflowA reference to return toSource dataMethods & versionsSettings & parametersReview decisionsThe reference stays intactRe-run & extendReuse methods. Keep every run traceable.RepeatExtendBatchSame methodNew run recordsCompare & refineCompare revisions and retain QC decisions.ReferenceProposed revisionData science & MLCurate examples, explore derived features,and develop models.CurateFeaturesTrainEvaluateNew behavior is evaluated before acceptance.

Consulting & ongoing engineering

Bring us the challenge.Let’s work through it.

Work with us on a technology decision, a defined project, or a continuing partnership. You can start with the systems you already use.

Practical expertise for your lab

  1. Choose what to invest in

    Compare software, equipment, and infrastructure against your lab’s requirements and future plans.

  2. Design and build what’s needed

    Improve workflows and lab services, connect software, and evaluate where automation or AI can help.

  3. Keep expertise close

    Combine ongoing technical planning, troubleshooting, and development as your priorities change.

Explore consulting & partnership

Built for the lab’s environment

Make the technology work together.

We coordinate machines, storage, access, and processing with your lab and institutional IT. Explore how the platform supports day-to-day work.

Institution-controlled
research data

Coordinated
IT & security review

Non-public research
confidential by default

For your institution

A conversation, grounded in your work

What would help your lab move forward?

Bring us an analysis bottleneck, a technology decision, or a capability you want to build. We’ll follow up to understand the work and discuss a useful next step.

Discuss your workflow