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BrainRun AI: Building an AI Platform with Multi-Model Chat, Knowledge Search and AWS Infrastructure

HomeProjectsBrainRun AI
BrainRun AI platform interface with multi-model chat and knowledge search

For BrainRun AI, Webzenz Switzerland delivered a complete AI platform with multi-model chat, document search (RAG), AI agents, credit billing and AWS infrastructure.

Overview

BrainRun AI is an AI platform that brings several language models, a user's own documents, AI agents and usage-based billing together in one application. Users can work with different models side by side, use their documents as a knowledge source and automate tasks with agents.

Webzenz Switzerland was responsible for the full technical delivery: architecture, frontend, backend, servers and deployment on AWS. The platform covers AI chat, document processing, knowledge management, AI agents, user accounts, subscriptions, credits and an admin portal.

Starting point

The platform had to combine several language models and data sources without losing control of cost, security or response times. It needed a modular architecture in which individual areas can evolve and scale independently.

Webzenz Switzerland built specialised backend services behind a central API gateway for this. Each service has a clearly defined task, from chat and document processing to billing.

Project at a glance

Project
BrainRun AI
Category
AI Platform
Client
BrainRun AI
Project type
AI platform (SaaS)
Scope by Webzenz Switzerland
Full delivery from architecture to operations
Hosting
Amazon Web Services (AWS)
Languages
German, English, French, Italian
Delivered by
Webzenz Switzerland, our Swiss partner

Services

  • AI development
  • Web development
  • Backend development
  • AWS cloud infrastructure

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What was built

Features and delivery

Multi-model chat

Chat with several language models, streamed responses and an evaluation pipeline for quality and cost.

Document search with RAG

Text extraction, OCR, chunking, embeddings and semantic search turn a user's own documents into a knowledge source.

Knowledge and context management

A combination of vector search, relational storage and caching for fast, relevant answers.

AI agents

Agents with versioning, scheduling, result management and an estimate of the credits required.

Web search as an extra source

Integrated web search adds current sources to what the models know.

Multilingual interface

Interface in German, English, French and Italian plus a translation service with a multi-level cache.

Subscriptions and credits

Stripe subscriptions combined with an internal credit system that reflects token usage and model costs.

Admin portal and security

Admin portal with roles, sign-in by email, Google and Apple, JWT, role-based access, rate limiting and audit logs.

Monitoring and scheduled jobs

End-to-end monitoring of metrics, logs and traces plus scheduled background jobs.

Role of Webzenz Switzerland

Scope of work

  • System architecture with microservices and an API gateway
  • Frontend development with Next.js and React
  • Backend development with Python and FastAPI
  • AI integration, RAG pipeline and model connectivity
  • Database design with PostgreSQL, Redis and vector databases
  • Servers, deployment and operations on AWS
  • Quality assurance, testing and monitoring
Technology stack

Technologies used

Frontend
  • Next.js 16
  • React 19
  • TypeScript
  • Tailwind CSS 4
  • shadcn/ui
  • Radix UI
  • Headless UI
  • TanStack Query
  • Zustand
  • React Hook Form
  • Zod
  • Recharts
  • next-intl
  • Bootstrap
  • Sass
  • Swiper
Backend and API
  • Python
  • FastAPI
  • Uvicorn
  • Gunicorn
  • Pydantic
  • HTTPX
  • Domain-Driven Design
  • REST
  • Async
  • API Gateway
  • Server-Sent Events
Database and data layer
  • PostgreSQL
  • SQLAlchemy
  • asyncpg
  • Alembic
  • Redis
AI and models
  • OpenRouter
  • Custom model runtime
  • vLLM
  • Model catalog
  • Token and cost tracking
Knowledge search and documents
  • Qdrant
  • pgvector
  • Embeddings
  • RAG
  • Tesseract OCR
  • PyTesseract
  • pypdf
  • PDFMiner
  • pypdfium2
  • Pillow
  • SearXNG
Payments and billing
  • Stripe API
  • Stripe Webhooks
Authentication and security
  • PyJWT
  • Google OAuth
  • Apple Sign-In
  • bcrypt
  • RBAC
  • Rate Limiting
  • Audit logs
Servers, cloud and hosting
  • AWS EC2
  • AWS RDS
  • AWS S3
  • AWS CloudFront
  • Docker
  • Docker Compose
  • Nginx
  • TLS
Monitoring and operations
  • OpenTelemetry
  • Prometheus
  • Grafana
  • Loki
  • Tempo
  • Sentry
  • PostHog
Quality assurance
  • Git
  • GitHub Actions
  • pnpm
  • pytest
  • pytest-asyncio
  • Playwright
  • Vitest
  • Testing Library
  • ESLint
  • Ruff
Outcome

Result

BrainRun AI is an AI platform that unites language models, a user's documents, agents and billing in one application. Its modular architecture makes it possible to add new models, features and markets without major rework.

The project shows that Webzenz Switzerland can deliver complex AI platforms end to end, from the user interface and backend services to the infrastructure on AWS.

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