OWL Intelligence Platform

OWL Intelligence Platform

Enables data housed in various databases, applications, and formats easier to access, link,match, and score with any other dataset while providing the necessary tools for data visualization and analytics for decision making.

Converting disparate data into actionable intelligence
Connecting Data to Power Wise Decisions
Discover Networks and Patterns

Data Technology

Connecting Disparate Datasets and Data Attributes

  • Structured Data
  • Unstructured Data
  • Documents
  • Audio
  • Video
  • API Connectivity
  • Batch
  • Single Manual Entry
  • Case Management Systems
  • Record Management Systems

Customer Data Integration Module

In addition to accessing data stored internally or remotely a powerful feature of OWL allows the user to add additional data they have acquired from other sources in real-time.

Custom data fields can be user added to any record or data attribute.

Note fields are available to be attached with data records.

Custom records can be added into the OWL User Data Vault, single entry or batch imported, and linked, matched, and scored to other datasets and data attributes already residing within OWL.

Audio and Video can be stored or attached to any record or data attribute with the user adding metadata information for searching.

OWL users can extract data from webpages, forums, bulletin boards and social networks as well as documents in formats, such as PDF, Word, HTML or txt files. Captured data from an entire website, collected data is logged and maintained with a screenshot and as text, images and scripting.

OWL Technology

At the core to the OWL Intelligence Platform are the internally developed OWL Real-time Intelligence Algorithm, OWL Data Point Prevalence Algorithm, OWL Parsing Logic Algorithm, OWL Data Source / Data Attribute Selector Algorithm and the OWL Multi-Attribute Query Algorithm.


The OWL Real-time Intelligence Algorithm compares, matches, links, and scores data records and data attributes in real-time from disparate data sources housed in OWL structured and/or unstructured databases or third-party databases accessed via API.

The OWL Data Point Prevalence Algorithm assigns scores based on Credibility of the Data Returned, Credibility of the Data Source, Degree of Closeness and Weight. The algorithm works in conjunction with pre-defined settings by the user. User manual scoring intervention at a record or attribute provides the user with the confidence in the data returned and the link relationship with other records and data attributes. Results are managed via the Data Point Prevalence Scale within the various Visualization views.

TheOWL Parsing Logic Algorithm reviews and analyse query variables and terms parsing this information to create relationships to one or multiple data sources working in tandem with the OWL Data Source / Data Attribute Selector Algorithm which provides the user a granular ability to select one or multiple databases to be queried in real-time..

The OWL Multi-Attribute Query Algorithm works as a keyword search integrated into the OWL search engine to search a keyword or combination of keywords of scanned documents, metadata description and data attributes.

OWL SaaS Compliant Worldwide

  • Meeting Local Compliance and Security
    • Keeping our client organizations data secure and country compliant in a multi-cloud environment.
    • Security Controls and Advanced Functionality at the core.
    • Built for mission critical workloads.
    • Cyber Security – Product Security – Encryption
    • Industry standard encryption methods including AES-256 for data at rest and TLS1.3 for data
      in transit protect your data assets.
    • The OWL Intelligence Platform technical team is ready to work with you globally to deploy
      your data.


  • us-east-1:

    Northern Virginia, USA

  • us-west-2O:

    Oregon, USA

  • ca-central-1:

    Montreal, QC, Canada

  • us-east-2O:

    Ohio, USA

  • us-west-1:

    Northern California, USA

  • ap-east-1:

    Hong Kong, China

  • ap-southeast-1:


  • ap-southeast-2:

    Sydney, NSW, Australia

  • ap-northeast-2:

    Seoul, South Korea

  • eu-central-1:

    Frankfurt, Germany

  • eu-west-1:


  • eu-north-1:

    Stockholm, Sweden

  • eu-west-2:

    London, England, UK

  • eu-west-3:

    Paris, France

  • eu-south-1:

    Milan, Italy

  • me-south-1:


  • af-south-1:

    Cape Town, South Africa

Google Cloud Platform

  • us-central1:


  • us-east1:

    South Carolina, USA

  • us-east4:

    North Virginia, USA

  • northamerica-northeast1:

    Montreal, Canada

  • southamerica-east1:

    Sao Paulo, Brazil

  • us-west1:

    Oregon, USA

  • us-west2:

    Los Angeles, CA, USA

  • us-west3:

    Salt Lake City, UT, USA

  • us-west4:

    Las Vegas, NV, USA

  • asia-east1:


  • asia-east2:

    Hong Kong, China

  • asia-northeast1:

    Tokyo, Japan

  • asia-northeast2:

    Osaka, Japan

  • asia-northeast3:

    Seoul, Korea

  • asia-southeast1:


  • asia-south1:

    Mumbai, India

  • australia-southeast1:

    Sydney, Australia

  • asia-southeast:

    Jakarta, Indonesia

  • europe-west1:


  • europe-north1:


  • europe-west2:

    London, UK

  • europe-west3:

    Frankfurt, Germany

  • europe-west4:


  • europe-west6:

    Zurich, Switzerland

Microsoft Azure

  • centralus:

    Iowa, USA

  • eastus:

    Virginia (East US)

  • eastus2:

    Virginia, USA

  • northcentralus:

    Illinois, USA

  • westus:

    California, USA

  • southcentralus:

    Texas, USA

  • westus2:

    Washington, USA

  • westcentralus:

    Wyoming, USA

  • brazilsouth:

    Sao Paulo, Brazil

  • canadaeast:

    Quebec City, QC, Canada

  • canadacentral:

    Toronto, ON, Canada

  • northeurope:


  • westeurope:


  • uksouth:

    London, England, UK

  • ukwest:

    Cardiff, Wales, UK

  • francecentral:

    Paris, France

  • germanywest-central:

    Frankfurt, Germany

  • germanynorth:

    Berlin, Germany

  • switzerlandnorth:

    Zurich, Switzerland

  • switzerlandwest:

    Geneva, Switzerland

  • norwayeast:

    Oslo, Norway

  • eastasia:

    Hong Kong, China

  • southeastasia:


  • australiasoutheast:

    Victoria, Australia

  • centralindia:

    Pune (Central India)

  • southindia:

    Chennai, India

  • westindia:

    Mumbai, India

  • japaneast:

    Tokyo, Japan

  • japanwest:

    Osaka, Japan

  • koreacentral:

    Seoul, South Korea

  • koreasouth:

    Busan, South Korea

  • outhafricanorth:

    Johannesburg, South Africa

  • uaenorth:

    Dubai, UAE

  • uaecentral:

    Abu Dhabi, UAE