Prediction projects rarely succeed in isolation. They require collaboration between domain experts, analysts, data scientists, and stakeholders. Yet most tools are built for individual use, creating friction when teams need to work together.

Kanva was designed from day one for collaborative work. Here’s how it works.

The Challenge of Collaboration

Traditional predictive modeling creates bottlenecks:

  • Notebook silos: Work happens in individual files that are hard to share
  • Version confusion: Which model is the latest? Who made that change?
  • Status blindness: Is training still running? Did it succeed or fail?
  • Handoff friction: Moving from exploration to production means rewriting everything
  • Review difficulty: Stakeholders can’t easily review or provide input

These issues slow down projects and lead to miscommunication.

Project-Based Organization

In Kanva, all work happens within projects. A project represents a prediction initiative from start to finish:

  • Datasets connected to the project
  • Feature engineering configurations
  • Trained models and their versions
  • Predictions and results
  • Team access and permissions

Projects provide a natural unit for collaboration. When you join a project, you see everything relevant in one place.

Real-Time Updates

Model training and data processing can take minutes or hours. Kanva keeps everyone informed with real-time updates:

Training Progress

When someone starts a training job:

  • All team members see the job appear
  • Progress updates stream in real-time
  • Metrics update as training progresses
  • Completion (or failure) is immediately visible

No more refreshing pages or asking “is it done yet?”

Data Processing Status

Data ingestion and feature engineering also report live:

  • Row counts as data loads
  • Validation issues as they’re detected
  • Transformation progress
  • Profiling results as they complete

Team Awareness

See what teammates are working on:

  • Who’s online in the project
  • What tasks are currently running
  • Recent activity feed

Cross-Platform Access

Kanva runs on:

  • Web browsers: Access from any machine
  • Desktop applications: Native experience for focused work

Your work syncs across platforms. Start an analysis on your desktop, review results on your laptop, share with stakeholders who use the web.

Enterprise-Ready Workflows

For organizations with compliance and governance needs, Kanva supports:

Access Control

  • Project-level permissions
  • Role-based access (viewer, contributor, admin)
  • Organization management

Audit Trails

  • Who created each model
  • When was training run
  • What parameters were used
  • Full version history

Review Processes

Enable approval workflows for:

  • Promoting models to production
  • Changes to feature engineering
  • Dataset updates

How Teams Actually Use This

Scenario: Churn Prediction Project

Week 1: Setup

  • Data analyst connects customer data sources
  • Business analyst reviews data profile
  • Domain expert flags data quality issues
  • Everyone sees updates in real-time

Week 2: Feature Engineering

  • Analyst creates initial features based on customer behavior patterns
  • Domain expert reviews and suggests improvements from business knowledge
  • Team iterates on feature set together
  • All changes tracked and visible

Week 3: Model Training

  • Analyst configures and launches training
  • Everyone monitors progress in real-time
  • Business stakeholder reviews initial results
  • Domain expert validates that explanations make business sense

Week 4: Refinement

  • Team discusses results, visible to all
  • Additional features added based on feedback
  • New model trained, compared to previous
  • Final model approved for deployment

Throughout this process, no one is blocked waiting for updates. Everyone sees progress as it happens.

Breaking Down Barriers

The goal of collaborative prediction isn’t just efficiency—it’s better outcomes:

  • Domain experts catch issues that pure technicians miss
  • Business stakeholders provide input before models are finalized
  • Data scientists focus on complex problems instead of status updates
  • Everyone understands what the model does and why

When collaboration is natural, teams work better together. Better teams build better models.

Get Your Team on Kanva

Prediction succeeds when it’s a team effort. Kanva makes that teamwork natural with real-time updates, project organization, and cross-platform access.

Ready to transform how your team builds predictive models? Learn more about Kanva.

This is part of our ongoing series on modern predictive practices. Subscribe to stay updated!