Outsourcing Services

How to Build Software Powered By Artificial Intelligence

Vertscend applies 32 years of experience in software development and data science to develop software with artificial intelligence (AI) capabilities.

The Essence of Developing Software with AI Capabilities

Development of software with AI capabilities implies building new software or evolving existing software to output AI analytics results to users (e.g., demand prediction) and/or trigger specific actions based on them (e.g., blocking fraudulent transactions). 

Supported by AI, an application can automate business processes, personalize service delivery and drive business-specific insights. According to Deloitte, 90% of seasoned AI adopters say that “AI is very or critically important to their business success today”.

Use Cases for Software with AI Capabilities

Business process automation

  • Chatbots
  • Search engines
  • Automated document generation
  • Optical character recognition engine for data extraction from paper documents
  • Job candidates screening and shortlisting

Production management

  • Predictive maintenance
  • Demand and throughput forecasting
  • Process quality prediction
  • Production loss root cause analysis

Customer analytics

  • Sentiment analysis
  • Customer behavior prediction
  • Sales forecasting

Risk management

  • Counterparty risk analytics
  • Potential damage prediction
  • Fraud detection

Supply chain management

  • Demand forecasting
  • Lead time forecasting
  • Inventory optimization

Personalized service delivery

  • Customer segmentation
  • Recommendation engines

Roadmap: Developing Software with AI Capabilities

The duration and sequence of the development stages will depend on the scale and the specifics of both basic software functionality and artificial intelligence you want to enrich it with. Below we present a generalized process outline based on Vertscend 32-year experience in software development and data science.

Feasibility study

Duration: 1 month

  • Outlining high-level software requirements (in case of new software).
  • Creating a proof of concept (PoC) for AI to check the technical and economic feasibility of enriching software with it, estimate the scope of work, timeline, budget, and risks.
  • Calculating ballpark ROI of AI implementation.

Vertscend best practice: To save on time and budget resources and increase the ROI of AI, we deliver a PoC to uncover possible AI-related roadblocks, such as low-quality data, data silos, data scarcity.

Business analysis to elicit AI requirements

Solution architecture design

Business processes preparation (in case of software development for internal use)


Software development (non-AI part)

AI module development

AI deployment

Maintenance and evolution of AI-powered software

Consider Professional Services for Development of AI-Powered Software

Consulting: software development with AI capabilities

Our consultants help:

  • Conduct a feasibility study on integrating AI into your software (potential benefits, risks, and costs).
  • Outline a risk management strategy to mitigate AI-related risks.
  • Outline a development, deployment and integration plan for building software with AI capabilities.
  • Choose an optimal sourcing model.
  • Select a fitting technology stack for software and its AI part prioritizing open-source frameworks to optimize development time and costs.

Outsourced development of software with AI capabilities

We cover all the stages of development:

  • Feasibility study (including PoC).
  • Business analysis: eliciting requirements for software and AI.
  • Software development: UX and design, front-end and back-end development, QA.
  • AI development: data preparation, ML model building, training and tuning.
  • AI integration with software, deployment (MVP and full-scale rollout) and testing.
  • User training.
  • Software maintenance and evolution.

Talents Required for Developing Software with AI Capabilities

Project manager

To outline a project roadmap, manage the software & AI development life cycle, and foster collaboration between business and tech stakeholders.

Business analysts

To analyze business and user needs and translate them into technical requirements for software, AI, and integration between them.

Data scientists

To cleanse data for AI and engineer features; to build, train, test, and validate ML models. Domain experience is preferred.

Data engineer

To deploy AI and monitor it in production.

UX and UI designers

To design wireframes, create user stories and UI prototypes for AI-driven software, following the principles of user-centricity.

Software developers

To build the software back end and front end and build and implement APIs necessary for integration with AI, and further evolve software

QA specialists

To design and implement a test strategy to validate software quality.

Sourcing Models of Developing Software with AI capabilities

All resources are in-house

Full control over the project, however, the lack of the required skills in AI is likely. Growing in-house AI capabilities can be a strategic decision if the development of software with AI functionality is a part of company-wide adoption of AI technologies.

All resources are in-house, except for data scientists

High control over the project and access to competencies unavailable in-house. If you’re looking to grow an end-to-end in-house team in the future, look for a resource vendor who provides knowledge sharing.

Confirm Project Viability, Then Invest

A feasibility study conducted by Vertscend will help you see the strengths of your large-scale project and potential threats to its success.

Our High-Tech Expertise

Advanced data analytics techniques and solutions

  • Big data solutions
  • Data science
  • Machine learning
  • Artificial intelligence (AI)

Innovative technologies

  • Internet of Things (IoT)
  • Blockchain
  • Computer vision
  • Augmented reality (AR)
  • Virtual reality (VR)

Software architectural patterns

  • Microservices architecture
  • Cloud-native architecture
  • Tiered architecture
  • Reactive architecture

Prominent Projects by Vertscend

The World's Largest PLM Software Development

Vertscend developed a product lifecycle management application powering 20,000 retailers, manufacturers, and suppliers in 110 countries.

Our Customers Talk

Vertscend Services for Large-Scale Projects

Project management consulting

  • Reviewing your current project management process.
  • Planning and implementing new project management practices and instruments that address management gaps.
  • Documenting project requirements and scope.
  • Planning resources needed to achieve project goals.
  • Estimating the budget based on the project scope.
  • Setting up a project schedule, planning iterative releases if needed.

Software consulting

  • Investigating all business workflows that must be covered by software.
  • Scoping software requirements, addressing conflicting requirements.
  • Helping choose between custom and platform-based software development.
  • Creating functional and architecture specifications.
  • Planning software integrations (10+ integrations may be required for business-critical systems).
  • Planning the infrastructure capable of supporting the required workload.

Dedicated team for large-scale software development

  • Providing all resources needed for project completion (a pool of 370+ software developers and 240+ other project roles).
  • An in-house Project Management Office.
  • Fully self-organized teams with no need for your interference in daily activities.
  • Transparent reporting according to the agreed schedule.

Staff augmentation


We can complement your project team with the following competencies:

  • Project management
  • Back-end and front-end programming
  • Software architecture
  • Testing and QA
  • DevOps
  • UX and UI design
  • Cybersecurity
  • Help desk

Get Expert Help for Large-Scale Software Development

With Vertscend, you get knowledgeable project management and skilled software engineering that positively impact the course and results of large-scale projects.

  • Project costs are reduced due to the fast development pace.
  • Project flow is coordinated and clear to all the involved participants.
  • The time-to-value is short, with the first release generally available in 4-6 months and further releases each 2-3 months.
  • Software under iterative development is available 99.99% of the time due to the well-established CI/CD process.
  • Risks of budget overruns and vague deadlines are minimized.