Stack Seekers
Most "AI products" are just ChatGPT wrappers with a login screen.
The AI SaaS market is exploding, but most founders are stuck at the prototype stage. They have a prompt, a demo, and no production architecture. The result: a fragile product that breaks under real usage, burns API credits, and cannot scale.
AI SaaS Development Capabilities
Production AI, not prototype demos.
LLM Architecture & Integration
OpenAI, Gemini, Claude, or open-source models — chosen based on your product needs, not vendor lock-in. Streaming, function calling, and structured output.
AI Guardrails & Safety
Output validation, content filtering, PII detection, and rate limiting. Your AI features behave predictably in production — not just in demos.
RAG & Context Pipelines
Retrieval-Augmented Generation that grounds AI responses in your actual data. Vector databases, embeddings, and semantic search for accurate, contextual outputs.
Cost Optimization
Prompt caching, model routing (cheap model for simple tasks, powerful model for complex ones), and usage analytics to keep API costs predictable.
Automation & Workflows
AI-powered automation that replaces manual workflows — classification, summarization, content generation, data extraction, and decision support.
Full-Stack SaaS Infrastructure
Auth, billing, deployments, monitoring — the complete SaaS stack around your AI features. Not just the AI part, the whole product.
AI SaaS Case Studies
From AI concept to production product.
Frequently Asked Questions
Do I need my own AI models trained?
No. Most production AI SaaS products use existing LLM APIs (OpenAI, Gemini, Claude) with RAG pipelines, fine-tuned prompts, and context management. Custom model training is only needed for very specific use cases.
How do you control AI API costs?
Multi-model routing (cheap models for simple tasks), prompt caching, response caching, and usage analytics. Most products see 60-80% cost reduction after optimization.
Can you integrate AI into an existing SaaS?
Yes. I add AI features to existing products — copilots, smart search, content generation, classification, and automation — without requiring a full rebuild.
What about data privacy and compliance?
I implement PII detection, data anonymization, and choose between cloud and self-hosted models based on your compliance requirements (GDPR, SOC2, HIPAA).
Ready to Build Your AI SaaS?
Stop building chatbot wrappers. Build a production AI product with proper architecture, guardrails, and scalable infrastructure. From concept to launched SaaS in weeks.