Custom AI Development Services
We engineer production-grade artificial intelligence systems that solve real business bottlenecks. From autonomous AI agents and retrieval-augmented generation (RAG) to custom LLM wrappers and AI SaaS products.
The Problem With Generic AI Tools
Off-the-shelf AI tools and simple wrapper scripts often fail in production. They suffer from latency issues, high API token expenses, data security risks, and unpredictable hallucinations that disrupt business logic.
To build commercial AI products, companies need robust systems with caching layers, structured schema outputs, fallback models, and scalable vector databases.
Our AI Engineering Approach
CookMyTech designs production AI applications from the ground up. We build custom pipelines that bridge large language models with your business data, databases, and APIs.
- ✔ Deterministic JSON output parsing
- ✔ Vector search with sub-100ms response
- ✔ Enterprise security & private data guards
- ✔ Automatic API token cost optimization
What We Build in AI
Autonomous AI Agents
Multi-agent orchestrations with function calling, external tool usage, and automated multi-step decision workflows.
AI Agent Services →Enterprise RAG Systems
Document Q&A engines querying PDF, SQL, and internal knowledge bases using vector embeddings and semantic search.
RAG Services →AI SaaS Products
Full-stack multi-tenant AI applications complete with Stripe subscriptions, rate limits, and usage analytics.
AI SaaS Services →AI Technology Stack
Related Engineering Services
Frequently Asked Questions
How much does custom AI development cost?
AI development costs vary based on model complexity, data pipelines, fine-tuning needs, and UI integration. CookMyTech provides transparent, fixed-scope sprint pricing starting with a clear technical specification.
Can you integrate OpenAI or Claude models into existing applications?
Yes. We design enterprise AI integrations using OpenAI API, Anthropic Claude, Llama 3, and open-source LLMs with secure API gateways, rate limiting, and cost optimization.
How long does it take to build an AI application or MVP?
A functional AI MVP or prototype with LLM integration can be shipped in 3 to 6 weeks depending on data preparation and system workflow requirements.
Do clients own the intellectual property and code?
Yes, 100%. Clients own all repositories, custom model prompts, pipeline code, and infrastructure configurations with zero vendor lock-in.
Ready to build custom AI software?
Talk directly with senior AI engineers to discuss your architecture, data, and timeline requirements.