An open-source human-in-the-loop AI system to orchestrate teams of experts and machines
Orchestra automates repetitive, rules-based project tasks so team members can focus on creative and analytical work, learn new skills, and mentor others.
Using a human-in-the-loop AI system like Orchestra will improve your project management processes, resulting in increased accuracy and consistency, less time coordinating projects, and more expert time in the areas they are uniquely positioned to work on.
With Orchestra workflows, you’ll better allocate your team’s expertise, improve communication across teams, and never miss another deadline.
Below we'll walk you through an example of how Orchestra could be used in a newsroom. Take a look at the example implementation in our documentation!
Orchestra’s major features that organize teams of humans + machines
Below are two images of the Orchestra dashboard, the launching point for expert workers.
Click to see how tasks move differently across the dashboard for core workers and reviewers.
B12 has open-sourced Orchestra as part of our goal to build a brighter future of work.
At B12 our mission is to help people do more meaningful work. The rise of automation in the workforce is one of the largest challenges society will face in the coming decades. B12 looks to use technology and AI as a force for good to build a brighter future of work. As a team we strive to create a transparent and collaborative work environment that enables us to build the best possible products for our customers, including websites and SEO.
We started in New York, but are now a fully distributed company with B12ers in Canada, Kyrgyzstan, Turkey, many US states, and beyond. We hope you will join us!
Orchestra is motivated by years of research into machine-mediated expert teams.
Flash teams by Retelny et al., a study in empowering managers to coordinate interactions between a team of experts contributing to a larger project. Review hierarchies work from Anand Kulkarni et al. and Daniel Haas et al. shows that machines can pair experts with other experts to improve work quality while facilitating mentorship.
Active learning, or human-in-the-loop machine learning, is the study of how machine learning model training can happen in concert with a domain expert completing their work.
In 2019, Bharadwaj et al. published B12's first paper on how we support constrained creativity in Orchestra through Dynamic Checklists, automated quality assurance, and contextual reviewer feedback.
In 2020, Rahman et al. published B12's second paper on how we built a mixed-initiative system to combine multiple sources of semi-structured information into a single structured action plan.