TuplOS® : A Pragmatic Approach to ML

Designed for Domain Experts, NOT developers or data scientists

tuplos solutions

Tupl’s goal is to facilitate the creation of complex automation utilities within any industry, with a fast turn-around time, all the while delivering a quality product that is stable, scalable and easy to maintain.

Easy Data ingestion

Easy Data
ingestion

Any existing information source or hardware element.

Simplified Maintenance

Simplified
Maintenance

Scalable and Highly available with minimum human intervention.

Easy Data ingestion

AI tasks done by non data scientists

Integrated Feature Engine and ML Toolkit.

Easy Data processing

Easy Data processing

Correlate and build your own stats from raw data.

Flexible UI

Flexible UI

Customizable UI with Integrated Reporting.

MLOps Architecture for Automation

TuplOS has three main components, one that deals with the control of resources (Infrastructure Layer), a second one in charge of Data processing and storage (Data Layer), and a Visualization layer that facilitates the creation of UI based applications (UI Framework).

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Our technology choice

TuplOS® is designed leveraging Open-Source Big Data components for storing and processing big datasets in a distributed fashion on large clusters of commodity hardware.

technology choice technology choice technology choice technology choice
video tuplos play video

ML Ops is not just about building AI systems, but operating them

Watch this 20-minute video in which Rafa Guerrero, Tupl's Head of ML covers the main machine learning concepts

Unified analytics and Viewer

Unified analytics and Viewer

advantage

It facilitates the creation of new UI applications from scratch, an API to connect to the different data sources and a set of ready-made widgets that can be dynamically added to configure customized views relevant to each use case in a very simple way.

advantage

More than 160 widgets available now. The list keeps growing as new widgets are added to address new required functionality.

Data ingestion & system integration

Data ingestion & system integration

advantage

Easy Data ingestion process of any existing information source, hardware elements or sensors, as it supports connectivity with dozens of different data endpoints via standard and custom connectors and enables formatting of those into a uniform format.

advantage

Based on Open-Source Big Data components for storing and processing big datasets in a distributed fashion on large clusters of commodity hardware. This accomplishes three goals: massive data storage, fast processing and at a low price point.

Features Engineering and Machine Learning Toolkit

Features Engineering and Machine Learning Toolkit

advantage

Features engine with capabilities to edit and calculate ML Features, including simple and complex definitions over other metrics of different nature as counters, KPIs, events, statistics or any other data sets.

advantage

ML Toolkit allows users to create Machine Learning models for Classification, Regression and Clustering. These models are trained using KPI/Features/Alert data that has been generated in previous stages of the Tupl Data Ingestion Pipeline

Action automation & orchestration

Action automation & orchestration

advantage

It allows the configuration and execution of external and internal actions, such as sending an email based on some criteria, integrating against a third-party ticketing system or interacting with external equipment to perform an action.

advantage

It supports two ways of configuring actions: a simple declarative way to define most of the actions and a more advanced mode that allows to write functions, also known as Function as a Service or just FaaS, in your preferred language.

Infrastructure Layer

Infrastructure Layer

advantage

It provides the necessary utilities for the efficient management of computing, storage resources, and all services in the cluster, both third party as well as Tupl proprietary services.

advantage

It leverages Kubernetes to manage the runtime resources and their usage. Also, it manages multiple underlying infrastructure services in cloud providers (AWS, GCP, Azure, Digital Ocean...), bare metal servers and private clouds.

Get a demo of TuplOS today

Get started and request a demo to learn how TuplOS can help you.

tupl automation by AI for Network Operations

Operations made simple with AI

Associations we belong to:

SmartCity Cluster Tupl O-Ran Alliance Tupl Technology Park of Andalusia Tupl Telecom infra project Tupl 5G Open Innovation Lab Ametic la voz de la industria digital Our EU values has been the seed to transform an idea and a dream proposed 20 years ago into a real bottom-up movement lead by the Global StartupCities initiative