The Explainable AI Assurance Platform for ML Models, Data and Deployments

The Lorykeet Platform provides confidence in your use of AI being trustworthy, accountable, transparent, and valuable.

KEY ADVANTAGES

Centralized management of models and data catalog

Explainable AI(XAI) and "What if" Counterfactual Analysis

Open platform allows for “bring-your-own” methods​

Proactive risk management

Humans in the loop

Overcome resistance and accelerate adoption​

Our technology allows you to test and deploy machine learning models that are trustworthy and actually trusted

ResponsibleAI

The Responsible AI Assurance Platform

Speed up AI adoption with AI outcomes you can explain and trust. Reduce risk and bias exposure. Meet regulatory compliance requirements.

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Centralized_MODEL

Centralized ML Models + Data Catalog

Provide a unified view of ML models and Data across all key stakeholders using Lorykeet’s intelligent model and data discovery. 

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Humaninloop

Humans in the
Loop

Humans-in-the-Loop aims to achieve what neither a human being nor a machine can achieve on their own. Platform foundation is set up such that it allows both AI and human subject matter experts to interact . 

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AI-Governance

Open AI Assurance Framework

Support for multiple ML frameworks and ML platforms. Support for multiple XAI, bias/fairness test methods. Easily add external ML model testing & validation methods aka BYOM - Bring Your Own Method.

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Building trust into and earning trust in your AI

Explainability Matters

There are two areas where trustworthiness is key to AI actually delivering value.  The first is adoption by the intended users.  “While the value of artificial intelligence is now undoubtable, the question has become how to best use it—and that often boils down to how much workers and end users trust AI tools.” – Deloitte 2023 Tech Trends. The second area is meeting risk management, customer needs, and compliance requirements. As McKinsey points out in its September 2022 article Why Businesses Need Explainable AI and How to Deliver It, “Explainability helps organizations mitigate risks.  AI systems that run afoul of ethical norms, even if inadvertently, can ignite public, media, and regulatory scrutiny.” Lorykeet’s platform has been designed and developed to address both of these needs.  Speed up AI adoption with AI outcomes, algorithms and predictions you can understand, explain, and in which you can earn trust. Reduce bias and discrimination, and achieve fairness goals. Demonstrate regulatory compliance.

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Centralized ML Models + Data Catalog

Effective AI Assurance Requires Enterprise-level Controls

Managing Al risk and compliance is an enterprise challenge. AI silos hinder trust and create unnecessary fragmentation and complexity. Lorykeet provides a unified view of ML models and Data across all key stakeholders using “intelligent model and data discovery.”  Machine learning models are 90% data and 10% code. Knowing what data goes into which model is critical to tracking model inventory and performance across the AI lifecycle.  Centralized documentation drives  visibility into enterprise-wide Al risk exposure and compliance assurance. Lorykeet becomes your system of record for AI.  With our unified, explainable AI platform you enable centralized and standardized Al governance effort. 

Humans in the Loop for all phases of the AI lifecycle

Responsible AI Requires Collaboration between Artificial and Human Intelligence

Humans-in-the-loop typically refers to bringing together AI and human intelligence to create machine learning models. Humans are involved with setting up the systems, tuning, and testing models so prediction and decision-making improves. Human in the Loop aims to achieve what neither a human being nor a machine can achieve on their own. Lorykeet enables humans in the loop to achieve good governance, risk management and compliance. The platform is designed to facilitate human “stakeholders” interaction with the models, data, and results and allow validation of outcomes continuously. At a time when vendors focus on tools for data scientists, Lorykeet’s approach fosters collaboration among data scientists, business experts and risk analysts to proactively manage and govern AI risks. The result is AI that is fully vetted and trusted for business adoption, and able to stand up to regulatory, policy and risk reviews.

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Supporting objective and independent analyses and audits

BYOM with Lorykeet’s Open & Comprehensive Platform

As AI deployments expand and grow, managing compliance risks will increasingly require objective and independent reviews.  Model assurance will become an important element in organization’s effectively and responsibly developing and using AI.  Anticipating this need, Lorykeet has been designed to support multiple ML frameworks and ML platform, as well to enable the use of multiple XAI, bias/fairness test methods. Clients can easily add external ML model testing & validation methods, aka BYOM - Bring Your Own Method.

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