Building a ai saas with Drizzle? Let us review it.
Expert code review for ai saas apps built with Drizzle. We fix Drizzle-specific security gaps, optimize performance, and handle deployment. From $19.
Common Drizzle issues we find
Real problems from Drizzle codebases we've reviewed.
Missing relation definitions
Tables defined without Drizzle relations, forcing manual joins and losing type-safe relation queries.
Unsafe raw SQL usage
Using sql`` tagged templates with unsanitized user input, or falling back to raw SQL strings that bypass Drizzle's query builder.
No migration workflow
Schema changes pushed to production without generating or applying Drizzle Kit migrations, causing schema drift between environments.
Incorrect schema types
Using wrong column types (e.g., text instead of varchar with length, integer instead of bigint for IDs) causing data truncation or overflow.
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 Drizzle 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 Drizzle 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 Drizzle?
Yes. We regularly audit Drizzle 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 Drizzle ai saas apps?
Common issues include missing relation definitions and unsafe raw sql usage on the Drizzle 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 Drizzle ai saas production-ready?
Start with our code audit ($19) to get a prioritized list of issues. For Drizzle ai saas projects, the typical path is: fix security gaps, address ai saas-specific requirements, optimize Drizzle performance, then configure deployment. We provide a fixed quote after the audit.
How long does it take to audit a Drizzle ai saas?
Our code audit delivers a full report within 24 hours. For Drizzle ai saas projects, we check security, architecture, performance, and deployment readiness across all Drizzle-specific patterns. Fixes are scoped separately with a fixed quote.
Related resources
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