SCOPA - scalable, explainable AI

SCOPA - scalable, explainable AI

An enterprise AI platform for scalable, explainable predictive analytics.

"SCOPA" is the original name for our Explainable AI Platform that provides high throughput, scalable, explainable predictive analytics.

SCOPA is now called Explainable AI Platform

Our platform allows us to deploy a suite of layered deep learning, ML, and algorithmic models, in an ensemble. The results of this can be reasoned-upon to answer very subjective questions about the input data holistically.  Models and algorithms are individually scalable, and each may identify or predict a specific outcome, but collectively they can answer more holistic questions. The orchestration of the models, data analysis and pipelining is contained and managed within the Explainable AI Platform.

Explainable AI Platform Features

Why "Explainable AI"?

AI should not be a black box. To engender trust it is imperative that consumers of machine learning predictive analytics understand how the AI reached its decision.

Whether for decision support or as a decision maker, an AI application must be able to explain itself and be accountable.

Explainable AI (XAI) is a burgeoning field in machine learning that tackles this challenge, so we, as ultimate end-users, have faith in machine intelligence and can strive for its continuous improvement. Our Explainable AI Platform  embraces explainability, providing insights into the decision making process of the predictive output that it has made in answering questions of the data, ultimately providing a fingerprint of the predictive qualities.

Scalable

Our Explainable AI Platform is built for scalability. Every model or algorithm deployed into the platform is containerised and individually scalable. Queuing and constraint theory allows us to dynamically scale models at every step in a prediction pipeline based on the performance and throughput required of that model.

Evolvable

Evolvability has been baked into the architecture as a 1st class concern providing a high degree of potential for customisation and extension. This makes it an extremely portable solution across diverse domains, and also allows the predictive model architecture to evolve as the problem space changes over time.

Deployable

Our Explainable AI Platform is deployable in cloud or on-premises, and can be used either on a fully managed SaaS basis or as an enterprise self-managed deployment in your own infrastructure. It also uses contemporary open-source architecture technologies, with full deployment automation. It can even be deployed on laptops for demonstrations or at-the-edge applications.

Use Cases

Our Explainable AI Platform is ideally suited to enterprise use-cases in a number of sectors, such as specialised media classification, industrial maintenance, agri-tech, and healthcare.

It has been deployed to classify terrorist and extremist propaganda imagery for the security services and the Home Office in the UK at scale.
Even for such a complex and multi-faceted challenge, a bare bones instance of it scored remarkable metrics (over 0.95 precision, 0.85 recall) with plenty of room for substantial improvement.

Our Explainable AI Platform can be deployed for use cases in industry such as railway track environment analysis, or for predictive maintenance.

In Agri-Tech is is suited to use-cases such as crop disease prediction, yield prediction, or pest analysis using for example, drone footage, or spraying-boom camera imagery.

In healthcare it can be used for novel image analysis such as bone fracture detection.

Please do get in touch if you would like to find out more.

Our Products

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Data Language AI is our suite of intuitive AI SaaS products that generic AI services cannot beat.
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Frequently Asked Questions

What is Explainable AI

AI should not be a black box. To engender trust it is imperative that consumers of machine learning predictive analytics understand how the AI reached its decision.

Whether for decision support or as a decision maker, an AI application must be able to explain itself and be accountable.

Explainable AI (XAI) is a burgeoning field in machine learning that tackles this challenge, so we, as ultimate end-users, have faith in machine intelligence and can strive for its continuous improvement.

How does SCOPA make AI explainable?

SCOPA embraces explainability, providing insights into the decision-making process of the predictive outputs that it has made in answering questions of the data, ultimately providing a fingerprint of the predictive qualities. With SCOPA, each predictive output can be explored visually using a simple user interface.

Is SCOPA portable to my domain?

SCOPA is an extremely portable solution across diverse domains & challenges. It is ideally suited to niche and specialised machine learning problems that commodity AI services cannot handle. Typical domains it is suited for include Industrial Maintenance, Healthcare, Agri-Tech, and Homeland Security - for example we have deployed SCOPA for classifying terrorist imagery for homeland security services, and have been working on a solution for bone fracture detection in medical imaging.

Why is SCOPA better than a bespoke in-house solution?

Building a production-ready AI solution goes well beyond the data science. Models need to be deployed, scaled, orchestrated, and monitored. In our experience what seems like a straight-forward data science problem, turns out to be 10% AI, and 90% engineering. The total cost of ownership of delivering a project of this nature should not be underestimated. With SCOPA the engineering has all been done for you, meaning a considerably lower total cost and faster to market solution. Depending on the domain, SCOPA may work out-of-the-box, for example in the analysis of terrorist, or extremist imagery for homeland security using the AI models we have already purpose-built. Alternatively we can work with you to develop the machine learning models to meet your own challenge. Either way, with SCOPA the engineering is done.