Knowledge Platform

Capture Human Expertise + Data from Silos into Digital
Knowledge and Create Knowledge Applications Faster

Successful digitization requires optimizing hundreds of global operations and decision flows across the enterprise. To deliver high-impact operational efficiencies, AI applications must capture your employees’ expertise in addition to data. Maana enables subject-matter experts to mathematically model their knowledge and combine that with data from across silos to create AI applications that help employees make better and faster decisions.

Build Knowledge

The Maana Computational Knowledge Graph™ is a network of models that create the digital knowledge layer of your enterprise. This digital knowledge demonstrates the relationships and interdependencies between various concepts that are key drivers of operations, such as ships, cargo types, ports, contractual agreements and more.

Models

Maana’s Computational Knowledge Graph™ uses the innovative approach that separates the structure of data from its content. This separation provides ‘fluidity of modeling’ within a graph and makes it possible to re-purpose any data into a relevant structure. The platform enables users to create structural models from your enterprise data and blend that with computational models that mathematically encode human expertise and are trained by subject-matter experts.

This digital knowledge layer combined with Maana’s AI algorithms, help subject-matter experts rapidly create AI-driven knowledge applications that optimize operations by providing recommendations into specific operations or decision flows.

Explore Our Platform

Maana represents knowledge in the form of models. The Maana Knowledge Platform™ is used by experts in the organization to optimize assets and decisions flows three times faster than any technology.

 

Using Maana to build a well optimization application.

Hydrate Knowledge graph through discovery, acquisition, profiling and indexing of data

PEOPLE - CONTAINER MANAGEMENT - BOOKING SYSTEM - VESSEL SCHEDULES - CONTAINER MANAGEMENT - BOOKING SYSTEM -
Data Sources

Knowledge Graph

Knowledge Graph

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Create models using Knowledge Assistants that follow our “user guided machine assisted” AI methodology

External Integration

Develop Knowledge Applications by leveraging models networked across all key decision points in a workflow

Knowledge Apps

Knowledge Apps

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Improve and accelerate decision making via Knowledge Apps. Answers are fed back into models as they continue to learn.

Models Are Reusable for Faster Development

Maana’s Knowledge Graph™ enables users to quickly build structural and computational models that illustrate the dynamic relationships between siloed information across organizations. These knowledge models illustrate all possible relationships between the vast array of knowledge inputs to accelerate optimization of decision flows.



The flexibility of the knowledge graph enables groups across an organization to leverage and build upon the initial knowledge graph to rapidly develop models for iterative collaboration.

The models created by one group can be reused and build upon by other groups, enabling enterprises to build thousands of models at scale. As more knowledge models are created, the time-to-value is accelerated even faster. These models are dynamic, and once operationalized into line-of-business applications, they learn and adapt based on the user’s behavior to provide continuous intelligence for day-to-day operations.

Knowledge Platform Whitepapers

Maana's Differentiation White Paper

How Maana’s Knowledge Platform Helps
Fortune 500 Companies Accelerate Digital Transformation

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Maana Q Solution Brief

Enhanced self-service capabilities for subject-matter experts.

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Computational Knowledge Graph

All available and relevant knowledge is digitally represented in the Maana platform in the form of models, which capture information and the relationships between it. Multiple models can be connected together to form an intelligent, relationship driven, easily searchable and scalable semantic Knowledge Graph.

This Computational Knowledge Graph sits at the core of the Maana platform and puts relevant knowledge – in the form of recommendations – at the fingertips of decision makers. In this way, the Knowledge Graph vastly accelerates decisions, improves the quality of decisions, and learns from outcomes, which improves recommendations over time.

Knowledge Graph screen

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Bots

Maana bots enable subject-matter experts to build AI-driven knowledge applications by assisting and automating many of the cumbersome steps of building structural and computational models. They can perform automatic event-driven actions or notify other bots or users to take certain actions.

Maana bots can perform tasks such as capture expert knowledge, integrate data into graph, extract complex knowledge from data, reason over knowledge and automate building machine learning models.

bots

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Knowledge Applications

Knowledge Applications use machine intelligence to augment user decisions, enhancing both the quality and the speed with which day-to-day decisions are made.

Specifically, these applications are tailored for business users and provide prebuilt analytic functionality for predictive maintenance, supply chain optimization, accounts receivable optimization, and more. Users can also build new, custom Knowledge Applications or extend existing ones to meet unique requirements.

Knowledge Applications screen

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Faster Knowledge Modeling

Knowledge, from Maana’s perspective, is captured in the form of reusable models, which capture information and the relationships between it. Knowledge modeling is the digital encoding of information/data together with human expertise to generate actionable recommendations that can then be fed into specific decision flows.

Maana Q architecture is built using GraphQL, which provides an increasingly popular interface to the Maana Computational Knowledge Graph, making it easier to integrate new and existing intelligent services and bots.

The Knowledge Bots automate many of the computational modeling performed by your data scientists, such as field classification, entity recognition and supervised machine learning. Now you can can accelerate developing models that power your Knowledge Applications.

Knowledge Modeling screen

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Extensibility

IT organizations should be able to integrate and extend any new, enterprise wide platform to their current technologies. Maana Q architecture is built using GraphQL which provides an increasingly popular interface to the Maana Computational Knowledge Graph, making it easier to integrate new and existing intelligent services and bots. The Maana Knowledge Platform can support traditional 3rd party ETL, data wrangling, visual analytics, dashboards etc. through plug-ins, libraries and REST APIs.

Knowledge exists in many forms which is required to support any backend system, such as Google’s TensorFlow, gridMathematica, or even a proprietary system through a pluggable interface. Users should also have access to the right tool for each job. Whether it is a Python-based optimization package or a complex, deep learning network, fluid integration and composition is necessary and available.

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Visual Search & Exploration

A Brand New Highly Intuitive User Experience

Provides subject-matter-experts and business analysts with a highly intuitive user experience that enables them to leverage self-service capabilities to easily:

  • Build, enrich, search, and visually explore the Maana Computational Knowledge Graph™  to understand the relationships and interdependencies between concepts such as wells , people and activities.
  • Dramatically enhances the utilization of the Maana Computational Knowledge Graph.