Business Platforms and AI
Organizations building complex business platforms and AI-driven systems rely on software to support core operations, decision-making, and long-term product evolution. These platforms often sit at the center of internal processes or customer-facing products and must adapt as business models change.
Such systems typically combine complex business logic, data-intensive workflows, and integrations across multiple tools and services. As usage grows, software architecture, data quality, and operational discipline become critical to maintaining performance and reliability.
Typical Challenges in Business Platforms and AI
Complex Business Logic and Evolving Requirements
Business platforms must reflect changing processes, rules, and policies. Without clear system boundaries, complexity grows quickly and slows further development.
Data Fragmentation Across Products and Teams
Data is often spread across multiple applications, services, and teams, making it difficult to maintain consistency and support reliable analytics or automation.
Scalability and Performance Under Growth
As platforms gain users and features, systems must scale without introducing instability or excessive operational overhead.
Long-Term Maintainability and Ownership
Many platforms are built to launch quickly but not to evolve over years. Poor structure and documentation increase risk as teams and requirements change.
What We Build for Business Platforms and AI
That support complex workflows and operational processes
That consolidate information and enable reporting, insights, and automation
Integrated into existing products and platforms
That connect platforms with external tools, services, and partner ecosystems
How We Approach Platform and AI Development
Architecture-First Product Thinking
We focus on system structure, data flows, and responsibilities before implementation to support clarity and controlled growth.
Engineering Decisions Grounded in Real Usage
Design choices are informed by expected usage patterns, data volumes, and operational constraints rather than theoretical models.
Scalability and Observability by Design
Platforms are built to scale predictably and remain observable in production, enabling teams to understand behavior and address issues early.
Ownership Mindset Beyond Initial Delivery
We design systems to be maintained and extended over time, supporting long-term product ownership.
Development Process
Let's ConnectBusiness platforms and AI systems require structured development that balances speed with long-term maintainability. Our process is designed to deliver working functionality iteratively while maintaining clear architecture and operational discipline.
We support platform teams through every phase of development, from concept to production operations and continuous evolution.
01
Discovery & Design
- Business requirements and user research
- Architecture and data modeling
- Technology selection and feasibility
- Delivery planning and prioritization
02
Iterative Development
- Feature development in short cycles
- Integration with existing systems and data
- Testing, validation, and quality assurance
- Performance optimization and scaling
03
Production & Evolution
Deployment to production, monitoring, and continuous improvement based on real usage patterns and evolving business needs.
Business Platform and AI Case Studies
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HrAst: AI-Powered HR Assistant for Streamlined Candidate Interviews
Sotex built HrAst, an AI-powered HR assistant that automates initial candidate interviews through virtual video screening and automated evaluation. The platform standardizes assessments, ranks candidates based on response quality, and enables branded interview portals for employers. As a result, companies reduce manual screening time, accelerate hiring decisions, improve candidate comparison, and create a more consistent and efficient recruitment process.
Accelerating Systematic Reviews with AI-Powered Research Automation
Sotex built an AI-driven research automation platform that streamlines systematic reviews from citation discovery to evidence mapping. The solution automates screening, removes duplicate records, and unifies fragmented workflows into a single research environment. As a result, researchers reduced review timelines by up to 60 percent, improved accuracy, and generated evidence faster to support reliable, data informed decisions.
AgroGuide – AI Assistant Empowering Farmers with Instant Agricultural Insights
We built a RAG powered AI assistant for AgroGuide that enables farmers to ask questions and receive clear, accurate answers in real time. The solution replaced manual browsing with concise, mobile friendly responses drawn from a trusted agricultural knowledge base. As a result, farmers access critical pest and treatment insights faster, improve decision making in the field, and engage more consistently with the platform.
Discuss Your Platform or AI System with Our Engineers
Whether you are building a new platform, evolving an existing product, or integrating data and AI capabilities, our teams can help assess architecture, scalability, and delivery options.