Building a ai saas with FastAPI? Let us review it.
Expert code review for ai saas apps built with FastAPI. We fix FastAPI-specific security gaps, optimize performance, and handle deployment. From $19.
Common FastAPI issues we find
Real problems from FastAPI codebases we've reviewed.
Blocking calls inside async endpoints
Synchronous database calls, file operations, or HTTP requests inside async def endpoints block the entire event loop, making your API unresponsive under load.
Missing authentication on endpoints
API routes that handle sensitive data or actions without any auth middleware — Depends() for authentication is simply not included in the route definition.
No CORS configuration
CORSMiddleware either missing (blocking all cross-origin requests) or set to allow_origins=['*'] (allowing any website to call your API).
Pydantic models without validation constraints
Request models that accept any string length, any number range, and any format. No Field() constraints, so invalid data flows through your system.
AI SaaS challenges to solve
Key ai saas concerns that AI-generated code often misses.
Cost management and unit economics
Every user action costs you real money in API calls. If a user generates 100 requests a day and each costs $0.05, that's $5/day per user — $150/month. Without token tracking, usage tiers, and cost optimization, your AI SaaS can lose money on every customer.
Upstream API reliability
OpenAI and Anthropic APIs have outages, rate limits, and variable latency. Your SaaS needs fallback providers, retry logic with exponential backoff, request queuing, and graceful degradation. AI tools build direct API calls with no resilience — one upstream outage takes your entire product down.
Prompt management and versioning
Your prompts are your product's core IP. AI tools hardcode prompts in the source code. You need a prompt management system with versioning, A/B testing capability, and the ability to update prompts without deploying code. A bad prompt update shouldn't require a rollback of your entire application.
Output quality and consistency
AI responses vary in quality, format, and accuracy. Your paying customers expect consistent output. You need output validation, structured output parsing, retry logic for poor responses, and quality monitoring. One hallucinated response in a customer-facing context can destroy trust.
What we check
Key areas we review for FastAPI ai saas projects.
API cost tracking — per-user and per-feature token usage monitoring
Upstream resilience — fallback providers, retry logic, circuit breakers
Prompt management — versioned prompts, separated from application code
Output validation — structured parsing, quality checks, error handling
Not sure if your app passes? Our code audit ($19) checks all of these and more.
Start with a self-serve audit
Get a professional review of your FastAPI ai saas project at a fixed price.
External Security Scan
Black-box review of your public-facing app. No code access needed.
- OWASP Top 10 vulnerability check
- SSL/TLS configuration analysis
- Security header assessment
- Expert review within 24h
Code Audit
In-depth review of your source code for security, quality, and best practices.
- Security vulnerability analysis
- Code quality review
- Dependency audit
- Architecture review
- Expert + AI code analysis
Complete Bundle
Both scans in one package with cross-referenced findings.
- Everything in both products
- Cross-referenced findings
- Unified action plan
100% credited toward any paid service. Start with an audit, then let us fix what we find.
How it works
Tell us about your app
Share your project details and what you need help with.
Expert + AI audit
A human expert assisted by AI reviews your code within 24 hours.
Launch with confidence
We fix what needs fixing and stick around to help.
Frequently asked questions
Can you review a ai saas built with FastAPI?
Yes. We regularly audit FastAPI ai saas projects and understand the specific patterns and pitfalls of this combination. Our review covers security, performance, and deployment readiness.
What issues do you find in FastAPI ai saas apps?
Common issues include blocking calls inside async endpoints and missing authentication on endpoints on the FastAPI side, combined with ai saas-specific concerns like cost management and unit economics and upstream api reliability. We check for all of these and more.
How do I make my FastAPI ai saas production-ready?
Start with our code audit ($19) to get a prioritized list of issues. For FastAPI ai saas projects, the typical path is: fix security gaps, address ai saas-specific requirements, optimize FastAPI performance, then configure deployment. We provide a fixed quote after the audit.
How long does it take to audit a FastAPI ai saas?
Our code audit delivers a full report within 24 hours. For FastAPI ai saas projects, we check security, architecture, performance, and deployment readiness across all FastAPI-specific patterns. Fixes are scoped separately with a fixed quote.
Related resources
FastAPI by Use Case
Need help with your FastAPI ai saas?
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