What you can build with FastAPI AI Kit
Pre-built infrastructure for common AI backends. Pick the scenario closest to yours and start building today.
AI Customer Support Backend
Deploy a FastAPI backend that handles customer queries with LLM-powered responses, escalation logic, conversation history, and token-aware billing — all pre-configured.
RAG Document Search API
Ingest PDFs, Markdown, and text files into a vector store, then expose a semantic search endpoint powered by your LLM of choice — with pgvector or Qdrant pre-configured.
SaaS API Backend
JWT auth, API key management, Stripe usage metering, rate limiting, and background jobs — the entire infrastructure layer for a SaaS API, pre-built and production-ready.
LLM API Gateway
Expose a unified `/v1/chat` endpoint that routes to OpenAI, Anthropic, or local models — with per-key auth, rate limiting, token tracking, and usage metering for internal teams or customers.
AI Code Review Tool Backend
Receive GitHub webhooks, queue long-running LLM analysis jobs via Celery, store results in Postgres, and stream findings back — all pre-wired in FastAPI AI Kit.
Document Processing Pipeline
Accept file uploads, process them asynchronously via background workers, extract structured data with LLMs, and store results — all in a battle-tested FastAPI pipeline.
AI Chatbot Backend
Multi-turn conversation management, session persistence, streaming replies, per-user rate limiting, and token-based billing — the complete backend for a customer-facing AI chatbot.
Internal Knowledge Base API
Index your internal documentation, Notion pages, or Confluence wikis, then expose a query endpoint your team can call from Slack bots, dashboards, or internal tools.
AI Sales Assistant Backend
Build an AI sales assistant that retrieves context from your CRM, prospect data, or call transcripts, and generates personalized responses — all with per-rep usage tracking.
Multilingual AI API Backend
Detect input language, route to appropriate LLM context, maintain per-language conversation history, and return localized AI responses — all with the kit's pre-built infrastructure.
AI Video Generator Backend
Video generation models run for seconds to minutes per job. FastAPI AI Kit handles the parts around the model call — auth, per-customer rate limits, async job orchestration, and usage-based billing — while you connect your generation provider of choice (Fal.ai, Replicate, or a self-hosted model).
AI Image Generator Backend
Whether you're calling Fal.ai, Replicate, or a self-hosted diffusion model, the surrounding infrastructure is the same: auth, rate limits, async jobs, and billing. FastAPI AI Kit provides that layer so the only new code is the call to your chosen generation provider.
AI Voice Agent Backend
Voice agents chain speech-to-text, an LLM turn, and text-to-speech per exchange. FastAPI AI Kit's session model, streaming support, and unified LLM layer handle the middle step and the conversation state; you plug in your STT/TTS providers of choice.
AI Email Assistant Backend
An email assistant needs context retrieval (past threads, CRM data), LLM drafting, and usage tracking per mailbox or seat. This maps directly onto the kit's RAG pipeline, unified LLM layer, and per-API-key billing.
AI Coding Agent Backend
Coding agents run long LLM analysis loops against a codebase and need to track tool-call state, not just a single prompt/response. The kit's background job system and streaming layer handle the async, long-running parts; you build the tool-calling loop on top.
AI Workflow Automation Backend
Automation platforms need reliable async execution, retries, and webhook triggers as much as they need LLM calls. FastAPI AI Kit's Celery pipeline plus its unified LLM layer cover both halves of that problem.
AI-Powered CRM Backend
An AI CRM feature needs to retrieve the right customer context (deals, notes, call transcripts) before generating anything useful. The kit's RAG pipeline and per-rep API key tracking are built for exactly this shape of problem.
AI Healthcare Backend
Healthcare AI backends need async processing, auditable data storage, and careful access control. FastAPI AI Kit provides the architectural pieces (async Postgres logging, per-key access control, background jobs) that make it easier to build a compliant system on top of — it does not itself provide HIPAA certification or a signed BAA.
AI Legal Assistant Backend
Legal AI tools live or die on citation accuracy — answers need to be traceable back to the source clause or document. The kit's RAG pipeline returns source references alongside every answer, which is the baseline requirement for this use case.
AI Recruiting Backend
Resume screening and candidate matching are RAG problems with a scoring layer on top: retrieve the relevant job requirements and candidate history, then have the LLM produce a structured score. The kit's structured-output extraction pattern and per-key tracking map directly onto this.
AI Backend Boilerplate
If you're evaluating boilerplates for an AI product broadly — not tied to one specific application — FastAPI AI Kit's core layer (auth, LLM abstraction, RAG, billing, background jobs) is the general-purpose starting point most AI backends need, regardless of the specific product built on top.
LLM Boilerplate
Calling an LLM API directly is a few lines of code. Making it production-ready — streaming, token tracking, provider fallback, retries, and billing — is the part most 'LLM boilerplate' searches are actually looking for. That's the layer FastAPI AI Kit ships.
RAG Boilerplate
RAG involves more moving parts than most tutorials show: chunking strategy, embedding caching, vector store selection, context injection, and source attribution. FastAPI AI Kit ships all of it wired together, with pgvector and Qdrant supported out of the box.
AI SaaS Boilerplate
The difference between an LLM demo and an AI SaaS product is usage-based billing, per-customer rate limits, and API key management. FastAPI AI Kit ships all three pre-wired to Stripe, so the SaaS mechanics are done before you write your first product feature.
AI API Boilerplate
Building an AI-powered API product means more than wrapping an LLM call — you need auth, versioning, OpenAPI docs, rate limiting, and metering as first-class concerns. FastAPI AI Kit is structured around exposing exactly that kind of API.