How to Develop AI Software
Project Roadmap, Team, Sourcing Models
Having 33 years of experience in data science and AI, Loginet knows how to create powerful software with artificial intelligence (AI) capabilities promptly and with minimal risks.
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, 94% of business leaders agree that “AI is critical to success over the next five years”.
Loginet helps both enterprises and product companies plan and build full scale AI solutions for 30+ different industries, including manufacturing, healthcare, energy, retail and wholesale, professional services,financial services, and telecommunications.
Use cases for software with AI capabilities
Business process automation
- Chatbots
- Search engines
- Optical character recognition engine for data extraction from paper documents
- Automated document generation
- Job candidates screening and shortlisting
Production management
- Chatbots
- Search engines
- Optical character recognition engine for data extraction from paper documents
- Automated document generation
- Job candidates screening and shortlisting
Customer analytics
- Chatbots
- Search engines
- Optical character recognition engine for data extraction from paper documents
- Automated document generation
- Job candidates screening and shortlisting
Risk management
- Chatbots
- Search engines
- Optical character recognition engine for data extraction from paper documents
Supply chain management
- Chatbots
- Search engines
- Optical character recognition engine for data extraction from paper documents
Personalized service delivery
- Chatbots
- Search engines
Consider Professional Services for Development of AI-Powered Softwar
Loginet applies 33-year experience in software development and data science to create solid software with AI capabilities.
Consulting: software development with AI capabilities
- Analyzing your business needs and eliciting requirements for a cryptocurrency.
- Analyzing your business needs and eliciting requirements for a cryptocurrency.
- Suggesting an optimal cryptocurrency type, architecture design and tech stack for the cryptocurrency solution.
- Suitable for apps with simple business logic, e.g., for holiday approval, event registration.
- Suitable for apps with simple business logic, e.g., for holiday approval, event registration.
Outsourced development of software with AI capabilities
- Analyzing your business needs and eliciting requirements for a cryptocurrency.
- Analyzing your business needs and eliciting requirements for a cryptocurrency.
- Suggesting an optimal cryptocurrency type, architecture design and tech stack for the cryptocurrency solution.
- Suitable for apps with simple business logic, e.g., for holiday approval, event registration.
- Suitable for apps with simple business logic, e.g., for holiday approval, event registration.
Why Choose Loginet to Deliver Software Powered by AI?
- Drag-and-drop workflow editor for creating custom workflows.
- Pre-built templates for typical workflows.
- Workflow-related emails and notifications.
- Workflow scheduling.
- Real-time dashboards with workflow status, progress, due dates, etc.
- Workflow analytics (e.g., workflows by type, complexity, average completion time).
- Workflow analytics (e.g., workflows by type, complexity, average completion time).
Typical Roles in Our AI Solution Development Teams
Loginet applies 33-year experience in software development and data science to create solid software with AI capabilities.
Domestic payments
To outline a project roadmap, manage the software & AI development life cycle, and foster collaboration between business and tech stakeholders.
Business analysts
To outline a project roadmap, manage the software & AI development life cycle, and foster collaboration between business and tech stakeholders.
Data scientists
To outline a project roadmap, manage the software & AI development life cycle, and foster collaboration between business and tech stakeholders.
Data engineer
To outline a project roadmap, manage the software & AI development life cycle, and foster collaboration between business and tech stakeholders.
UX and UI designers
To outline a project roadmap, manage the software & AI development life cycle, and foster collaboration between business and tech stakeholders.
Software developers
To outline a project roadmap, manage the software & AI development life cycle, and foster collaboration between business and tech stakeholders.
Data engineer
To outline a project roadmap, manage the software & AI development life cycle, and foster collaboration between business and tech stakeholders.
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
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.
Non-AI part is developed in-house, while the AI part is outsourced
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.
PM and BA are in-house, all technical resources are external
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.
Complete outsourcing
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.
Benefits of AI-Powered Software Development with Loginet
- Drag-and-drop workflow editor for creating custom workflows.
- Drag-and-drop workflow editor for creating custom workflows.
- Drag-and-drop workflow editor for creating custom workflows.
- Drag-and-drop workflow editor for creating custom workflows.
- Drag-and-drop workflow editor for creating custom workflows.
- Drag-and-drop workflow editor for creating custom workflows.
- Drag-and-drop workflow editor for creating custom workflows.
Get Expert Help to Build Software with AI Capabilities
Our team can help! We can also assess whether the integration project is worth your time and money and which integration scenario will bring max benefit.
Cloud Services Loginet Uses to Speed Up Development of AI Solutions
AI platforms help quickly set up, automate and manage each stage of the AI module development with pre-configured infrastructure and workflows. ScienceSoft recommends considering platforms by major cloud providers: Amazon, Microsoft, and Google. All of them are leaders in Gartner’s Magic Quadrant for Cloud AI Developer Services and offer integrated development environments (IDEs) with the following capabilities:
- Drag-and-drop workflow editor for creating custom workflows.
- Pre-built templates for typical workflows.
- Workflow-related emails and notifications.
- Drag-and-drop workflow editor for creating custom workflows.
- Pre-built templates for typical workflows.
- Workflow-related emails and notifications.
- Workflow scheduling.
Cost Factors of Developing Software with AI Capabilities
- Drag-and-drop workflow editor for creating custom workflows.
- Pre-built templates for typical workflows.
- Workflow-related emails and notifications.
- Workflow scheduling.
- Real-time dashboards with workflow status, progress, due dates, etc.
- Workflow analytics (e.g., workflows by type, complexity, average completion time).
- Workflow analytics (e.g., workflows by type, complexity, average completion time).
- Workflow analytics (e.g., workflows by type, complexity, average completion time).
- Workflow analytics (e.g., workflows by type, complexity, average completion time).
- Workflow analytics (e.g., workflows by type, complexity, average completion time).
Sample costs
$100,000-$200,000
For an AI-powered solution that automatically extracts unstructured data from several sources, classifies it using an ML algorithm of modest complexity, and provides outputs in batches.
$500,000-$650,000
For an AI-powered solution that automatically extracts unstructured data from several sources, classifies it using an ML algorithm of modest complexity, and provides outputs in batches.
Get the exact cost estimates for your AI project
Loginet’s team will be glad to provide a custom quote for your specific case.
