FastAPI at Shivacha
High-performance Python API framework with type-driven validation.
Overview
FastAPI uses Python type hints for validation and automatic OpenAPI documentation, with async support for high concurrency. It is our default for Python APIs, especially AI inference and orchestration services.
Why we use it
- Type-driven validation
- Automatic OpenAPI docs
- Async performance
- Great for AI services
How we use it
FastAPI in our engineering work
AI APIs
Serving LLM and ML capabilities.
Microservices
Lightweight Python services.
Data APIs
Exposing analytics and features.
Services
Services that use FastAPI
AI Development
End-to-end AI development: from use-case selection and data preparation to models, applications and production operations.
Learn moreLLM Development
LLM application and platform engineering: model selection, fine-tuning, serving, evaluation and cost-optimised inference.
Learn moreAPI Development
Design and build secure, well-documented APIs that power your apps, partners and integrations — REST, GraphQL and real-time.
Learn moreGenerative AI Development
Generative AI applications for text, documents, code and media — grounded in your data and engineered for production reliability.
Learn moreRAG Development
Retrieval-augmented generation systems that ground LLM answers in your documents with permissions, citations and measurable accuracy.
Learn moreAI Chatbot Development
LLM-powered chatbots for customer service, sales and internal support — grounded, on-brand and integrated with your systems.
Learn moreProducts
Products built with FastAPI
Pairs well with
What we combine with FastAPI
Languages and frameworks for APIs, services and business logic.
Insights
Related insights
Designing AI products users trust
Trust in AI products is designed: show sources, make uncertainty visible, make correction easy and keep humans in control of consequential actions.
Learn moreAI development cost: what you pay for when you build an AI product or agent
Model fees are rarely the main cost. Data preparation, evaluation, integrations and guardrails decide both the budget and whether the system works.
Learn moreWhy most AI pilots never reach production — and the engineering that fixes it
The model is rarely the problem. Retrieval quality, evaluation, integration and governance decide whether an AI pilot becomes a production system.
Learn more
Build with FastAPI.
Tell us about your project, or the engineers you need, and we will propose an approach.