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Unlock the power of your data silos to drive your competitive advantage.

  • Nebuli’s Datastack® combines your siloed data sources and analytics tools, with optional public-cloud data services, into a single technology stack.

  • Open up unlimited possibilities for your team to turn your data silos into actionable results through Nebuli’s federated learning models.

Datastack’s integration framework allows teams to untrap their data from multiple sources combining them into complete and accurate datasets for digital business processes and sophisticated data analysis.

We help customers employ our Datastack framework to integrate the traditionally separate business-critical data services, such as data security, compression, modelling, classification, segmentation, knowledge discovery and much more, into an API-powered integrable service.

Nebuli's Datastack Framework - unlocking value from siloed datasets and AI services, supporting hybrid cloud infrastructures.

Key Benefits

Data Migration

Strategic data preprocessing and migration from legacy database models and file archives to integrable cloud databases.

Data Readiness

Data catalog assessment for achieving successful digital transformation strategies.

Hybrid Cloud Integration

Offering efficient hybrid cloud integrations, combining your on-premises servers or private cloud with public cloud services.

Data Security

Enhancing data security protocols and data privacy policies through our Nebulized Data Layer.

Data Ethics

Examining data, privacy and technological commitment toward ethical and trustworthy alignment with personal and cultural concerns.

Policy Audit

Aligning regulatory and internal policies with the fast-moving digital transformation and AI-driven world.

The Datastack is about data quality, not just quantity.

Our mission with the Datastack is to establish a new standard that helps teams and organisations uncover new business opportunities and hidden augmented intelligence capabilities through their trapped data that can dramatically transform their output across markets.

We help you explore your data pain points and work with you in defining your ultimate data-driven outcomes by producing the right metrics and conditions for your end-users.

Data Security with the Nebulized Data Layer.

Security and data privacy are the most critical elements of Nebuli’s entire ecosystem and are at the heart of the Datastack framework.

The Nebulized Data Layer® (NDL) is our innovative data security layer that completely circumvents the need for customers to upload copies of their original data.

The NDL forms the central part of the Datastack and contains a customer’s indexed data needed for sepcific tasks. The system then compresses this indexed dataset into its internally generated semantic and ontological models that allows it to read data in any format, language and from any vertical.

The NDL processing generates Nebuli’s unique machine language that offers superior data compression, flexibility, speed and security to customers’ “Nebulized” data. This layer eliminates any footprints leading back to the customer’s original data sources.

The NDL Process:

  • 1.

    Customer dataset pre-processing – creating data description maps to allow Nebuli algorithms “understand” the datasets.

  • 2.

    Data extraction – indexing the critical data parameters needed by Nebuli for a given task without storing the rest of the data.

  • 3.

    Data Decomposition – breaking down the indexed datasets into smaller tasks that can be parallelised within Nebuli’s operations.

  • 4.

    Further Extraction of “useful” data parameters – where Nebuli selects subsets of data indices to built its “Data-Driven World”.

  • 5.

    Final normalisation of the extracted data – to reduce data redundancy and improve data integrity, while forming Nebuli’s internal representation of the customer’s data.

Our Datastack framework operation is independent of any data formats, platforms and languages.

For customers, this offers an unmatched, more accessible, personalised and faster cross-disciplinary and cross-regional data integrations and interoperability.