Poolside + AI Wrapper / LLM App

Built a ai wrapper / llm app with Poolside?
We'll make it production-ready.

AI wrapper apps — products built on top of OpenAI, Anthropic, or other LLM APIs — have unique production challenges. The AI model is a black box that's slow, expensive, and unpredictable. Your app needs to handle variable response times, API failures, cost management, and output quality control in ways that standard web apps don't.

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AI Wrapper / LLM App challenges in Poolside apps

Building a ai wrapper / llm app with Poolside is a great start — but these challenges need attention before launch.

API cost management

LLM API calls are expensive. A single unoptimized prompt can cost cents per request — which adds up fast with real users. You need token counting, cost tracking, usage limits per user, and prompt optimization to stay profitable.

Response time variability

LLM responses take 1-30 seconds depending on prompt complexity, model load, and output length. Your UI needs streaming responses, loading states, and timeout handling. Users abandon apps that feel slow.

Error handling for AI responses

The AI model might: return an error, time out, return malformed output, refuse to answer, or hallucinate. Each case needs specific handling. AI tools build the happy path but not the many failure modes.

Prompt injection and security

Users can manipulate your AI's behavior through carefully crafted inputs — making it ignore instructions, reveal system prompts, or produce harmful output. Input sanitization and output validation are essential.

Rate limiting and queuing

LLM APIs have rate limits. When many users make requests simultaneously, you need a queue system to manage the flow and provide feedback to waiting users. Without this, users get API errors during peak usage.

Output quality control

LLM responses aren't deterministic — the same prompt can produce different quality results. You need output validation, retry logic for poor responses, and potentially human review for critical outputs.

What we check in your Poolside ai wrapper / llm app

API key security — LLM API keys stored server-side, never exposed to client
Cost controls — per-user limits, token counting, usage monitoring
Streaming implementation — proper SSE/streaming for LLM responses
Error handling — timeouts, rate limits, model errors, malformed output
Prompt injection protection — input sanitization, output validation
Rate limiting — user-level and application-level limits
Caching — caching identical or similar requests to reduce costs
Monitoring — cost tracking, latency tracking, error rates

Common Poolside issues we fix

Beyond ai wrapper / llm app-specific issues, these are Poolside patterns we commonly fix.

highSecurity

Code-only focus misses authentication requirements

Poolside generates high-quality application code but doesn't add authentication, authorization middleware, or access control by default — leaving API endpoints and data unprotected.

highCode Quality

Generated code may not fit your project's architecture

Poolside produces idiomatic, high-quality code, but without deep knowledge of your project's specific architectural patterns, the generated code may conflict with your established service layers and module boundaries.

mediumDeployment

No deployment or infrastructure awareness

Poolside focuses on application code and does not generate Dockerfiles, deployment scripts, environment configuration, or CI/CD setup. Production deployment requires separate work.

mediumSecurity

Input validation present in generated code but not at API boundaries

Poolside validates data within functions but may skip HTTP-layer input validation — allowing malformed or oversized payloads to reach application logic before being caught.

Start with a self-serve audit

Get a professional review of your Poolside ai wrapper / llm app at a fixed price.

External Security Scan

Black-box review of your public-facing app. No code access needed.

$19
  • OWASP Top 10 vulnerability check
  • SSL/TLS configuration analysis
  • Security header assessment
  • Expert review within 24h
Get Started

Code Audit

In-depth review of your source code for security, quality, and best practices.

$19
  • Security vulnerability analysis
  • Code quality review
  • Dependency audit
  • Architecture review
  • Expert + AI code analysis
Get Started
Best Value

Complete Bundle

Both scans in one package with cross-referenced findings.

$29$38
  • Everything in both products
  • Cross-referenced findings
  • Unified action plan
Get Started

100% credited toward any paid service. Start with an audit, then let us fix what we find.

Frequently asked questions

Can I build a ai wrapper / llm app with Poolside?

Poolside is a great starting point for a ai wrapper / llm app. It handles the initial scaffolding well, but ai wrapper / llm apps have specific requirements — api cost management and response time variability — that need professional attention before launch.

What issues does Poolside leave in ai wrapper / llm apps?

Common issues include: code-only focus misses authentication requirements, generated code may not fit your project's architecture, no deployment or infrastructure awareness. For a ai wrapper / llm app specifically, these issues are compounded by the need for api cost management.

How do I make my Poolside ai wrapper / llm app production-ready?

Start with our code audit ($19) to get a clear picture of what needs fixing. For most Poolside-built ai wrapper / llm apps, the critical path is: security review, then fixing core flow reliability, then deployment. We provide a fixed quote after the audit.

How much does it cost to fix a Poolside-built ai wrapper / llm app?

Our code audit is $19 and gives you a complete report of issues. Fixes start at $199 with our Fix & Ship plan. For larger ai wrapper / llm app projects, we provide a custom fixed quote after the audit — no hourly billing.

Get your Poolside ai wrapper / llm app production-ready

Tell us about your project. We'll respond within 24 hours with a clear plan and fixed quote.

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