Business Model

Product Strategy or Custom Engineering - PRADA engine does the heavy lifting.

Your Needs, Our Solution

Transformation of problems into tenable solutions is greatly simplified through code automation. Entrust Vittena with your technology specific needs and let us exceed your expectation.


Well positioned for a greenfield application development from concept phase.


Capable of service-to-service integration of two distinct applications or build a new API to engage them.


Supercharge under-performing or under-scaled legacy applications by transforming the design architecture and rebuild it.

Supported Architectures

Capable of building most suitable architecture designs prevalent in the industry. The bottom-up design strategy provides for enhanced resilience to cater to the domain specific needs. The coding engine has been designed to orchestrate both conventional and modern needs.

Micro Service

Based on every domain specific need, the PRADA engine is articulated to generate database suitable for microservice architecture.


PRADA engine helps generate a codebase compatible to the serverless design patterns and capable of rapid deployments in Microsoft Azure or AWS Lambda Serverless elastic environment.


Automated coding engine delivers layered, closely knit and well-connected modules to form a business-critical apps, the generation engine produces bulky volumes of code bases to form one whole monolith stack.

Client Server

Based on the requirements and deployment environment, the generated output code base can be augmented to handle the anticipated load from the clients.

Requirement Engine

Inbuilt requirements engine systematically channelizes numerous problem statements and transforms into both high level and low-level requirements. Entire requirements are pruned through an automated input, output and dependency mapping engine to create a robust data model.

Requirement Analysis and Design Review

Using the declarative metadata modelling technique, clustered data models woven through an entity relationship employing hundreds of nodes. Such designs are automatically skewed to fit the kind of architecture the domains require.

Business Requirement

So formed techno-functional design shall be vetted and redesigned by the business analysts to ensure conformance to business use cases.

Domain Specific Review

Value added domain expertise shall fine tune the business logics and functional outcome iteratively until expected results are delivered.

Technical Review

The auto generated tabulations and entity relations shall be technically vetted by experts to approve in conformance with functional & non-functional requirements.

Schema Generation Engine

Intelligent constellation of entity relation and database structure is then transformed into scriptified schema so that the coding engine will have a terms of reference.

Coding Engine

Code automation engine now parses through the schema definition to understand the resultant source code base. The coding engine develops 15 visible layers of source code for each entity.

Code Augmentation

Aptly created placeholder created within the generated code base allows developers to manually augment code gaps.

Business Logic

The only manual coding area whereby every specific business rules are written with the predefined placeholders.

Service API

Entity specific API Layer helps seamless transaction among various inter-entities and other external applications.


Vue Js presentation layer template gets generated with model, API and constants. Manual augmentation needed on Directives, objects and validation.

Quality Assurance Engine

Guaranteed for negligible bugs or defects due to machine coding, automated test cases based on requirements. User Interface, API and functional testing fully automated with the exception reports, business rules and business validations.

Automated Testing

Rules driven test cases and functionalities get generated based on predetermined scenario matrix.

Defect Report

Automated exception reports as a resultant of a scenario checklist precisely guiding the developer to buggy areas.

Efficiency Analysis

Intuitive analytics of test efficiency and key metrics to call out the test engine efficiency.

Deployment Engine

The deployment engine has been designed to build, bundle and deploy in the user defined service provider infrastructure as a seamless process. A fine-grained configuration and setup module need to be provided with infra and portability information for automated deployment.

On Premise

Based on your internal policies and economies, the build release can be fully deployed within native test or production environment without compromising security.

On Cloud

Built using the most modern technologies, the build release is truly cloud ready and effortlessly deployed on Microsoft Azure, AWS Lambda, Google Cloud or with similar managed service providers.


Define which business entities need to remain on-premise and which other on-cloud while remaining continuously integrated to make the solution multi-tenant and concurrent.

Technology Stack

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