Besegma: AI Copilot for Predictive Analytics

With Besegma, we partnered on implementing AI capabilities into a product focused on predictive analytics. The startup had strong domain expertise but needed a practical assistant layer to help users work faster with complex analytical outputs and turn insights into action. Our role was to design and deliver an AI copilot that improved real workflows, not just demonstrate model potential in isolated scenarios.

The implementation combined TypeScript, React, and Node.js with integrations to OpenAI API and Claude API, supported by Python components for data-heavy processing paths. A key part of the architecture was prompt orchestration, context validation, and response quality control. We needed the copilot to produce useful, consistent outputs aligned with product expectations, while still allowing flexibility for different analytical tasks. The feature set was connected directly to core product actions so users could summarize, investigate, and decide faster.

A central challenge was balancing generative flexibility with trust and interpretability. In predictive analytics, users must understand why a recommendation appears and what context informed it. We implemented structured response patterns, transparent context handling, and safeguards for sensitive data flows. We also designed the system for iterative extension, making it easier to introduce new integrations and specialized assistant capabilities as product requirements evolved.

The collaboration continued beyond the initial release phase, with ongoing expansion of the main product and additional service integrations. The delivered work strengthened Besegma’s product position and contributed to recognition including Best ICT Solution at the CommsBusiness Awards 2025.