Skip to main content

Architecture & technology overview

This page gives you a high-level overview of how CallPilot.ai is built and the main technologies behind the platform.

The goal is to help technical stakeholders (CTOs, architects, developers) understand how CallPilot.ai fits into a modern cloud and AI ecosystem.

High-level architecture​

CallPilot.ai is a cloud-native platform designed around:

  • A modern web frontend for supervisors, admins and operators.
  • Backend services that handle campaigns, flows, integrations and analytics.
  • AI services to understand and generate natural language.
  • Cloud infrastructure that is secure, scalable and observable.

At a high level, a typical flow looks like this:

  1. Users configure campaigns and flows from the web app.
  2. Backend services store and manage configuration, contacts and results.
  3. For voice and messaging, CallPilot.ai connects to telephony / messaging providers.
  4. For AI capabilities, CallPilot.ai uses OpenAI models and Azure Search for knowledge retrieval where applicable.
  5. Metrics and logs are collected for monitoring and reporting.

Frontend: React + Vite​

The CallPilot.ai application used by your team (supervisors, admins, operators) is built with:

  • React – A modern UI library for building complex, interactive interfaces.
  • Vite – A fast build tool and dev server, optimized for React and TypeScript.
  • TypeScript – Adds static typing to JavaScript for better reliability and DX.

What this means for you:

  • A fast and responsive user interface.
  • A modern stack that is easy to extend and integrate.
  • Consistent user experience across different modules (campaigns, flows, reporting, etc.).

Backend services​

Under the hood, CallPilot.ai uses a set of backend services responsible for:

  • Managing campaigns, flows and channels.
  • Handling contact lists and interaction outcomes.
  • Integrating with external systems (CRMs, core systems, etc.).
  • Exposing APIs and webhooks for developers.

These services are primarily built with:

  • Node.js and Python – Popular ecosystems for APIs, automation and data processing.
  • REST APIs with OpenAPI documentation – So developers can easily discover and integrate endpoints.

Data is typically stored in:

  • PostgreSQL – For relational, structured data (campaigns, configuration, accounts, etc.).
  • MongoDB or similar NoSQL stores – For flexible, document-style data and logs where needed.

AI and knowledge: OpenAI + Azure Search​

CallPilot.ai uses AI to power advanced capabilities such as:

  • Intelligent call and message flows.
  • Dynamic responses based on customer input.
  • Retrieval of domain-specific knowledge.

Key components:

  • OpenAI models – Used for understanding and generating natural language.
  • Azure AI Search – Used as a semantic search engine and knowledge layer:
    • Indexes documents and knowledge bases.
    • Supports semantic and keyword search.
    • Provides relevant context to AI agents during a conversation.

This combination allows CallPilot.ai to:

  • Answer complex questions using your own data.
  • Adapt flows based on customer intent.
  • Provide more natural and consistent interactions.

Cloud & infrastructure​

CallPilot.ai runs on Microsoft Azure and uses managed services to ensure reliability and security, for example:

  • Containerized services (e.g. Azure Container Apps / Kubernetes-based workloads) for scalability and isolation.
  • Azure Storage for files, logs and artifacts.
  • Observability through logs, metrics and dashboards to monitor system health.

Depending on your setup, CallPilot.ai may connect to:

  • Telephony providers (e.g. for voice calls).
  • WhatsApp providers for messaging campaigns.
  • CRMs and core systems via secure APIs or integrations.

Integration points​

From a technical perspective, CallPilot.ai integrates with your stack via:

  • APIs

    • Create and manage campaigns.
    • Upload contact lists.
    • Query results and analytics.

  • Webhooks

    • Receive events such as:
      • Campaign or call completed.
      • Message delivered or failed.
      • Survey responses and outcomes.

  • Connectors / integrations

    • To CRM or core systems when available.
    • To data platforms for reporting.

You can explore the concrete endpoints and schemas in the Developer Guide and the API Reference (/api).

Why this matters for you​

Knowing the technologies behind CallPilot.ai helps you:

  • Evaluate how it fits your existing tools and standards.
  • Plan integrations with your CRM, core systems and data warehouse.
  • Understand performance, security and scalability characteristics.

If you need more technical details (networking, security controls, or specific architecture diagrams), please reach out to your CallPilot.ai contact or support team.