Leveraging all the features present in Qvantia, every business can make the most out of data and models. It helps to streamline the development process, maintaining the models in production in the long run. No more patchy solutions, with the high risk of open-source. No more endless iterations between colleagues. No more suicide in production due to the lack of governance. No more hand-made AI, thanks to that brings AI into adult life.
Qvantia provides a unified ML and AI platform, empowering organisations to operate throughout the steps of ML and AI.
It has the flexibility to nurture the data scientists’ creativity, operationalise the deployment, and automate the orchestration of monitoring and retraining.
It enables the collaborative design of AI application, seamless integrated with data, experiments and models. Qvantia is not the umpteenth MLOps solution, but an end-to-end ML and AI platform that allows organisations to create scalable and reliable applications, better defining mission critical AI applications, usable in everyday tasks.
ML and AI are collaborative. Qvantia makes AI projects collaborative since inception, with a shared design of the solution leveraging drag-and-drop functionality. It seamlessly integrates within experiments and modelling, smoothing the code preparation and optimisation. With Qvantia you forget the usual bumps along the road, preparing for the performance monitoring part.
Based on multiple research reports, AI solutions have a severe issue with time-to-market. The average payback is 19 months, making investing in AI challenging to sustain.
Qvantia measures the progress on the whole lifecycle of development, highlighting potential bumps or hiccups along the way. The collaborative approach we envision is central to calculating the effort generated and its performance compared to planning.
Artificial Intelligence solutions are not islands; they exist because of the eco-systems where they operate. Qvantia shares the existing objects composing AI solutions between projects and teams. Exploration of AI objects is easy, either tabular or graph-based, expediting the process.
Potfoglio is actionable, defining the following action to develop a consistent and scalable AI solution.
Object reusability reduces the costs of creating the AI application, increasing the ROI.
We envision a future where Artificial Intelligence permeates every aspect of our lives. AI will reshape our lives and think, from autonomous vehicles to tailored movie selection. One of the most significant challenges in AI resides in the ability to control the end-to-end life cycle. From data acquisition to the monitoring of models, Qvantia is a silent partner that stands with you every step of the process.
Qvantia delivers the right data at the right time in the right place. Moreover, it cleans and prepare the data for experiments and modelling.
Turning data into insights is a joint activity that starts with exploring data. Business users and technical experts collaborate to generate the new dataset for modelling.
Labelling data is one of the most critical and time-consuming tasks in ML. Qvantia offers a mix of machine-based and manual data labelling, building the consensus of rightly labelled target variables.
Qvantia provides a comprehensive check for data quality based on the principle that ML and AI models are as good as their data quality. Offline and online assessments are in place to feed just good data.
Experiments are at the heart of Qvantia, helping to create the best AI solution. Seamlessly integrated with the data acquisition layer, experiments will give data scientists the flexibility to explore and create efficient models.
One of the essential steps of ML and AI is the deployment of models. Qvantia smooths the process of making them available, ensuring that infrastructure performance is consistent.
One of the main objectives of Qvantia is monitoring model performance based on metrics and KPIs shared throughout the collaborative process of implementing AI solutions.
We recognise the massive impact of drift on the model performance. Qvantia takes care of retraining models whenever necessary, reducing the costs of maintaining the solutions up and running and tackling data and concept drifts.
A collaborative framework to design effective and reliable AI models. Business users and technical experts collaborate to define the life cycle.
From data to experiments and modelling. An easy process to move from idea to exploration and modelling, without the hassle of exhausting iterations.
Move models in production, and measure the performance and the results. Continuously monitoring the new data and events, retraining the models when necessary.
It's all about the humans behind a brand and those experiencing it, we're right there. In the middle.
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