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ShabdizSHABDIZ
PROTECT

Data protection and privacy

Keep data flowing;
keep identity under control.

Shabdiz controls sensitive information visibility in APIs, databases and datasets according to organizational policy, keeping data usable for testing, development, analysis and exchange.

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Policy-based protectionData format awarenessDeployment within your organization
Data before and after the protection policySHABDIZ
Choose a protection method01 — POLICY
Conceptual illustration Format preservation using synthetic data
FieldOriginal dataPolicy output
NameMaryam AhmadiUser 482
Mobile091200000000912•••••••
Customer ID1200486258320714
Service typeSupportSupport
Format-aware8-digit ID → 8-digit ID

In this example, the numeric ID keeps its length, the name is pseudonymized and the mobile number is masked.

The service type is retained so work can continue.
Conceptual illustration · Synthetic dataINPUT → POLICY → OUTPUT
DATA PRIVACY & ANONYMIZATIONFrom data source to point of use

A closer look

Product brochure & demo

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Product demo Shabdiz

Behind the name Shabdiz

From swiftness and vigilance to protecting identity

World-ranging, moving at the speed of thoughtAware as the night, awake as the dawn

Nezami, Khosrow and Shirin, section 18

Shabdiz, the night-dark horse from the tale of Khosrow and Shirin, is known in Nezami’s poetry for its swiftness and alertness—a horse that traverses difficult paths and whose movement the poet likens to the speed of thought. Shabdiz symbolizes motion with vigilance.

For us, the name Shabdiz recalls this pairing: data must keep flowing, serve development and analysis, and lay the groundwork for better decisions; yet not every destination needs to see every identity. The value of data lies in its use, and trust and vigilance in protecting what must not be revealed.

The Shabdiz system turns this perspective into a protection policy: sensitive information is anonymized or made fictitious during exchange or dataset preparation, according to the consumer’s needs. An appropriate method and output validation help the data remain usable with the same appearance and structure as the original data, while keeping identity disclosure under control.

Data continues on its way; identity travels with it only as needed.

01At a glance

What is Shabdiz and where is it used?

A layer between data owners and consumers to control what becomes visible.

What is it?

A data protection and privacy system

Shabdiz processes sensitive fields through masking, pseudonymization, hashing and format-aware transformations. Protection methods are selected according to use and destination.

When?

When data must be used but identity exposure must stay limited

For test data, API exchange, contractor collaboration or data preparation for analytics and AI, especially when technical access alone should not permit viewing every detail.

For which organization?

Any organization holding sensitive information

Banking and insurance, operators, public services, healthcare and data-driven businesses: wherever customer, citizen, employee or partner information moves between teams and systems.

For decisions and execution

Security and data leaders, enterprise architects, database, development, API, testing, analytics and AI teams.

02Key capabilities

The right protection method for each type of data.

Method selection starts with consumer needs: what must remain visible, what must change and which relationships must be preserved?

Policy-driven01

A policy for each path and destination

Define which field is transformed, for which consumer and by which method.

PII / API / DestinationDefined policy
Masking02

Conceal all or part of a value

Control sensitive data visibility according to consumer needs.

091200000000912•••••••
Pseudonymization03

Substitute identities for data use

Replace direct identifiers with pseudonyms in operational or analytical scenarios.

Maryam AhmadiUser 482
Hashing04

One-way transformation where appropriate

When recovery is unnecessary, design a hashing method appropriate to the data type.

Input identifierHashed value
Format-aware / FPE05

Transformation that considers data format

Suitable transformations account for the length, type and pattern required by the destination system.

1200486258320714
Deterministic06

Consistent transformation across records

Within a consistent scope and policy, repeated identifiers receive the same substitute to preserve record relationships.

A → AB → B

Examples illustrate the methods; operational policies depend on data types and destination-system requirements.

03Two use areas

One Shabdiz, for data flows and data stores.

Flow and Vault are two uses of one product. Choose an area to see its data path, inputs and outputs.

Data in Motion

Protection along the data exchange path

When data moves between APIs, services or organizational systems, protection policies apply during exchange so consumers receive only the information they need.

REST APIJSON / XMLAPI GatewayService-to-Service
  1. 01Source API or service
  2. 02Protection policy
  3. 03Shabdiz core
  4. 04Protected response
Input
API requests or responses and messages processable in the service layer
Output
Protected payload for the destination service or authorized consumer
Suitable use
System-to-system exchange, contractor integration and structured input for AI workflows
Deployment point
API gateway or organizational integration layer, depending on the project architecture

Protection with usability

The right format.
Usable output.

Protecting data while destroying the required structure also stops testing or analysis. Shabdiz chooses transformations with regard to data type, length and pattern.

With consistent transformations and compatible policies, relationships between records can also be preserved so the destination team can continue working with the data.

Transformation example preserving ID lengthFORMAT-AWARE
Original identifier8 digits
12004862
SHABDIZ POLICY
Transformed identifier8 digits
58320714
Type: numericLength: preservedValue: transformed

Conceptual illustration with a synthetic identifier

04Use scenarios

Data reaches its destination under that destination’s policy.

01TEST & DEVELOPMENT

Realistic testing with controlled identity exposure

QA teams need data with a usable structure.

Expected output

A transformed copy for development, testing and UAT.

Vault
02API & INTEGRATION

Each service gets what it needs

API consumers do not need all personal information.

Expected output

A protected response based on that path’s policy.

Flow
03DATA SHARING

Share data with contractors

Support and collaboration require data, while identity visibility must remain limited.

Expected output

A payload or dataset suited to the other party’s use.

Flow + Vault
04ANALYTICS & AI

Control data before analytics and AI

Personal identifiers may enter analytics or AI workflows together with the data.

Expected output

Transform sensitive fields before structured data enters the consumption pipeline.

Flow + Vault

05From policy to execution

Protection as a traceable process.

We start by understanding the source and deliver output assessed against both organizational policies and consumer needs.

  1. 01

    Understand the data

    Identify sources, structure and sensitive fields.

  2. 02

    Define policies

    Choose protection methods based on data, use and destination.

  3. 03

    Execute transformation

    Apply policies in the API path or dataset processing.

  4. 04

    Validate and deliver

    Check format, output quality and consumer functionality.

  5. 05

    Monitor and review

    Log operations and update policies as requirements change.

Schema-awareAttention to data structure and type
Batch processingBatch dataset processing
Audit & loggingOperation logs for traceability

06Integration and deployment

In your environment, with a defined scope.

Shabdiz works independently of other Faraconesh products. Starting with one API path or dataset enables output evaluation and gradual expansion.

ON-PREMISES / PRIVATE

Protection close to the data

Deploy in organizational infrastructure or a private environment, aligned to confidentiality requirements, service architecture and access controls.

MySQLOracleAPI / JSON / XML

Development and deployment experience exists on MySQL and Oracle; versions, data types and connection methods are determined in the technical review.

What is needed to start?
Sample data or its structure, a list of sensitive fields, the consumption path and expected output.
What is reviewed?
Source version, volume and exchange rate, format rules, access permissions and the need for reversible transformation.
How does the scope expand?
After validating quality and performance, policies extend to additional sources and consumers.

Fits into your organization’s data path

Depending on the scenario, Shabdiz can provide data protection alongside other products.

SimurghData for AIShahbazData for behavior analyticsHodhodProtection during data collection

Before you start

Frequently asked questions

Choose protection methods by understanding the data and consumer needs.

Automatic playback · Paused

No. Shabdiz has no editions. Flow and Vault are two uses of one product: protecting data in transit and stored data. A project may cover either or both.

Start with your challenge

Where should the data go,
and what should remain hidden?

Let’s identify your data sources, consumption path and protection needs, then explore the right Shabdiz scope together.

Start exploring your needsTalk to the Faraconesh team