Bledar BunjakuBledar BunjakuSoftware Engineer / Available for contract work
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Vaenso Energy Analytics and Service Platform

Vaenso is a Norway-based energy analytics and service platform with dashboards, onboarding, backend services and AI-assisted user workflows.

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ReactTypeScriptNestJSPostgreSQLOpenAIAnthropicSSES3-compatible storageDomain-Driven DesignFile uploads

Role

Bledar worked across backend architecture, APIs, AI chatbot features, onboarding flows and frontend dashboards.

What to verify

Built backend services for energy metering and facility management.

Result

Delivered backend services, APIs, onboarding and dashboard functionality for a real energy platform.

Problem

Energy platforms need reliable onboarding, integrations, metering workflows, facility data and responsive user-facing dashboards.

My role

Bledar worked across backend architecture, APIs, AI chatbot features, onboarding flows and frontend dashboards.

Main features

  • Energy metering and facility management services
  • Onboarding system with external Elhub integration
  • AI chatbot with multi-provider support
  • Real-time engagement using Server-Sent Events
  • File upload system with S3-compatible storage
  • Frontend dashboards

Architecture

  • React and TypeScript frontend.
  • NestJS backend with modular Domain-Driven Design.
  • PostgreSQL persistence.
  • LLM provider integrations with OpenAI and Anthropic.
  • SSE for real-time engagement.

Technical decisions

  • Used modular backend architecture for maintainability.
  • Supported multiple AI providers rather than locking the product to one model vendor.
  • Used SSE where server-to-client engagement updates were sufficient.

Challenges

  • Integrating external energy data workflows.
  • Coordinating AI chatbot behavior with product-specific user flows.
  • Keeping onboarding and dashboard features coherent across the stack.

Results or impact

  • Delivered backend services, APIs, onboarding and dashboard functionality for a real energy platform.
  • Added AI-assisted features and real-time engagement capability.

What I would improve next

  • Add deeper monitoring around external integration failures.
  • Document measurable AI chatbot usage and success metrics.