A Mission to Elevate Work

We provide groundbreaking AI software to automate predictable decisions and work, while learning to assist people with more complex work and decisions. We do this by observing conditions, behaviors, and their outcomes.

At OnCorps, our mission is to elevate work and performance by applying AI to handle predictable and laborious calculations, decisions, and tasks. We provide advanced AI solutions to the financial services industry, where we have substantially reduced manual work, errors and risk. We solve problems with cross-disciplinary teams, drawn from top-tier research universities and consultancies, and possessing industry, data science, and computer science expertise. Our pioneering algorithms have shown dramatic results. Our operational AI systems have reduced labor costs by over 90 percent. Our algorithms have identified millions in errors. And our forecasting systems have consistently beaten client forecasts. Our success has led to strong demand, attracting clients with over $11 trillion in assets under management. Our innovative algorithms have earned us the 2019 NOVA Award by NICSA and the 2019 Fintech Breakthrough Award for best banking infrastructure software. Our business model has also achieved breakthrough results. We leverage state-of-the-art cloud technologies to design workflows, train algorithms, and integrate with legacy systems. Expert, cross-disciplinary teams deploy these technologies rapidly. In all cases, our clients have paid no external consulting fees nor required internal technical team support. We believe results from AI can only be achieved by providing constant, high-end support. We provide process, algorithm, and systems support delivered by the same team that designed the solution. This simple difference reduces significant inefficiencies and elevates our service far beyond that of any other firm. We are committed to delivering the most cutting-edge solutions possible. To accomplish this, we work closely with scientific advisors from Yale, Harvard, and Oxford to formulate and rigorously test new algorithms. Our work in behavioral AI has been published in the Harvard Business Review and other journals.

Core Principles

We are a problem solving culture

  • Challenging assumptions, testing hypotheses, and constantly curious
  • Commanding expertise in technical and mathematical techniques
  • Seeking to close gaps in performance and decisions

We seek only exceptional people

  • Demonstrating significant prior academic and professional distinction
  • Embodying a tenacious and persistent character
  • Operating with humility and a sense-of-humor

We are committed to craftsmanship

  • Believing that our standard is perfection
  • Mastering industry based AI solutions
  • Nurturing expertise in the latest algorithms and tools

We are relentlessly improving

  • Learning from errors and seeking better solutions
  • Making minor adjustments to boost performance
  • Constantly identifying variances and inconsistencies

We lead from the front-lines

  • Assigning leaders who excel in the work they lead
  • Rewarding problem solvers over administrators
  • Keeping teams small, empowered, and flat

We strive for ethics and quality

  • Selling solutions that provide value
  • Seeking always to do the right thing
  • Striving to be ethical in our work

Business Model

Fixed Fee Customization. Changes in agile development, open sourcing, and cloud virtualization enable us to rapidly customize our platform. We develop customized decision guidance systems for a fixed fee. The fee includes developing algorithms and management dashboards, customizing UI/UX, API configuration, security testing, and user acceptance testing.

High-End Subscription Support. Once we deliver a production pilot, we offer ongoing support with the same team that configured the pilot. Our customers pay a platform fee and per app fee for this support. These subscription fees include support for data scientists, delivery managers, and engineers who monitor engagement rates and algorithms.

Conservative Algorithm Use. We almost always start systems using Policy Settings. These settings don't rely on algorithms, but instead enforce leadership-defined policies and thresholds. Once algorithms gain more consistency and accuracy, we can selectively use algorithms to trigger workflows and recommendations.

Current Economic Model

OnCorps Model

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