Signals AI & Integration Hackathon

Frequently Asked Questions

Participant Requirements & Team Composition

To ensure a productive and hands-on experience, attendance is limited to 20 participants total. Organizations may register up to 4 participants per company, including:

• 1–2 developers (required) who will be responsible for building and coding the solution.
• Up to 2 additional team members serving as Product, Design, Business, Scientific, or Domain Subject Matter Experts.

Development Expectations

• Teams will design and build a working integration, application, or AI-enabled solution during the hackathon.
• Developers may use the programming language of their choice; however, Python is recommended due to its extensive support for AI, data science, and API development workflows.
• Additional technical guidance, development resources, and any required pre-event setup instructions will be provided prior to the event.

Required Experience

• All participants should be familiar with the Signals platform and its core capabilities.
• At least one developer on each team should have prior experience with Signals APIs, integrations, or platform extensibility options. Teams without prior experience are strongly encouraged to review available API documentation and integration resources before the event.
• Participants should be prepared to actively contribute throughout the day in a collaborative, technical environment.

What to Expect

This is a working session rather than a lecture-based event. Participants should come prepared to:

• Write code and build prototypes.
• Collaborate closely within cross-functional teams.
• Rapidly test, iterate, and demonstrate solutions.
• Present their team's results during the final showcase and demo session.

Example Use Cases

Automating repetitive lab setup

Turning a handful of user choices into hundreds of correctly configured records, for example, generating all the containers and scheduled tasks needed for a stability study (samples × storage conditions × timepoints), or registering an incoming shipment of 100 materials and creating a container for each batch, in one action instead of hundreds of clicks.

Smarter tables and calculations

Adding configurable calculation columns to tables from a template library, or moving selected data between tables in an experiment through a simple interface rather than manual copy-paste.

Closing the loop on results

Automatically feeding test results from downstream test experiments back into the originating experiment, so the requester sees their data without chasing it.

Reporting and search-driven output

Building a plug-and-play report engine, or generating a consolidated report from a search result spanning many experiments: names, attributes, purpose/discussion/conclusion, reactions.

Notifications and proactive alerts

Using the notification engine to warn stockroom managers about containers approaching expiry, or to flag any date-driven event before it becomes a problem.

Connecting Signals to the tools you already use

Pushing tasks into Outlook or Google Calendar; integrating with ACD/Lab; linking synthesis steps so a product from one experiment becomes the reactant of the next; Create your next experiment step from previous experiment reaction step...