SERVICES
More than software. A partnership in science.
DataJoint isn't a tool you deploy and figure out alone. At your option, engagements are led by our SciOps team; scientists and engineers who specialize in scientific data operations.
From first conversation to production deployment to ongoing partnership, we work alongside your researchers, not in parallel to them.
MEET THE SCIOPS TEAM
Scientists who specialize in scientific data.
Our SciOps team blends neuroscience PhDs, infrastructure engineers, and operations specialists. We don't hand you the platform and walk away. We deploy alongside you, transfer knowledge to your team, and support your work as your science evolves.
Scientific Depth
Our team includes neuroscience PhDs who understand experimental design, multimodal data, and the real challenges of complex R&D workflows.
Engineering Excellence
Infrastructure engineers and data architects who deploy DataJoint cleanly into your environment, integrate with your existing systems, and maintain operational rigor.
Hands-On Partnership
Engagement isn't transactional. We work alongside your team, transfer knowledge, and stay engaged as your work evolves and scales.
HOW WE ENGAGE
Three phases. One proven engagement.
Every DataJoint engagement follows three phases: Design, Build, and Launch. The phases give your team a clear arc from first conversation to production. The detail within each phase keeps the work concrete.
Design
DISCOVERY & ARCHITECTURE
Every engagement starts with deep consultation. We understand your science, your data, your pipelines, and your integration landscape. By the end of Design, you have a clear technical blueprint and an agreed-upon engagement plan.
WHAT HAPPENS HERE
- Collaborative Pipeline Design
- Systems Integration
Build
CONSTRUCTION & CONFIGURATION
This is where the engineering happens. Our SciOps team constructs your DataJoint pipeline, configures the infrastructure, and builds the interfaces your researchers will use. Every step preserves data integrity and prepares the foundation for production.
WHAT HAPPENS HERE
- Orchestration Configuration
- Continuous Integration & Deployment
- Notebook Environments
- Graphical User Interfaces
Launch
VALIDATION & ONGOING PARTNERSHIP
The foundation goes live. We validate everything end-to-end, train your team, and stay engaged as your science evolves. This phase doesn't end at handoff. Launch becomes ongoing partnership.
WHAT HAPPENS HERE
- Testing
- Training & Ongoing Support
Three phases. One proven engagement. From first conversation to ongoing partnership, the methodology stays consistent so the outcomes stay predictable.
WHAT THIS PRODUCES
Outcomes from disciplined engagement.
When engagement follows a documented methodology, outcomes become predictable. Here's what happens when DataJoint engages.
Production-ready in under 60 days
Most pilots reach production deployment within 60 days of engagement kickoff.
Knowledge stays with your team
We don't just deploy. We transfer knowledge so your scientists can operate the foundation independently.
Scales as your work scales
The foundation grows with your research. Same architecture, more pipelines, more outcomes.
Audit-ready from day one
Provenance, lineage, and reproducibility are built into the methodology. No retrofitting compliance.
DISCIPLINES
Expertise across four disciplines.
Our SciOps team draws expertise from four disciplines that intersect at the heart of modern R&D: life sciences, computer science, data science, and operations.
Life Sciences
Multi-modality investigation of biological systems including neuroscience, behavior, oncology, omics, kinematics, and more. Our team has worked on the hardest scientific problems.
Computer Science
Reproducible pipelines, automated processing, end-to-end governance of the data supply chain. Engineering excellence applied to scientific challenges.
Data Science
Signal extraction, quality control, computational methods, AI/ML analysis. Turning raw experimental data into scientific insight.
Operations
Operational excellence applied to scientific work. Maximum efficiency, scalability, and reduced errors through disciplined operational practice.
READY TO START THE CONVERSATION?