Asad Ali — Co-Founder & CTO, ZTABS. Co-founder and CTO of ZTABS. Writes about LLM systems, vector databases, and the operational reality of running production AI.
Co-Founder & CTO, ZTABS
Asad Ali
Asad Ali is the co-founder and CTO of ZTABS. He leads the engineering organization and is personally responsible for the architecture decisions on the firm's largest and most technically demanding engagements — the ones where customers cannot afford a wrong call on which LLM, which vector database, or which deployment topology to bet on.
Asad publishes on the ZTABS blog when he has something concrete to add to a discussion that the broader internet is getting wrong or oversimplifying. His work tends to focus on the gap between vendor marketing and what actually happens in production: where retrieval-augmented generation breaks under real workloads, why self-hosting an LLM is more expensive than the calculator pages claim, what vector database benchmarks miss, and which architectural patterns survive contact with messy enterprise data.
Before ZTABS, Asad shipped large-scale distributed systems and led engineering teams at multiple stages of growth. He is hands-on enough that on most weeks he still writes production code, runs incident reviews, and pairs with newer engineers on the firm's hardest problems.
If you are reading a ZTABS article that includes a hard operational number — a benchmark figure, a cost ceiling, a failure mode — Asad's standard for letting it ship is "would I be willing to defend this number to a customer's board?" If the answer is no, the number doesn't go in.
Areas of expertise
- Large Language Model Integration
- Retrieval-Augmented Generation
- Vector Databases
- Self-Hosted LLM Operations
- Distributed Systems
- Cloud Architecture
- Production AI Operations
Find Asad elsewhere
Email: asadali.ztabs@gmail.com
Recent articles by Asad Ali
AI Development
Function Calling in LLMs: How AI Agents Use Tools (Practical Guide)
Function calling (tool use) is what gives AI agents the ability to interact with the real world — searching databases, calling APIs, and taking actions. This guide covers how function calling works across GPT-4o, Claude, and Gemini, with code examples and production patterns.
14 min read
AI DevelopmentHow to Fine-Tune an LLM: Complete Guide to Custom Model Training (2026)
Fine-tuning an LLM gives you a model that speaks your domain's language. This guide covers when to fine-tune, how to prepare data, and step-by-step instructions for OpenAI and Hugging Face.
19 min read
AI DevelopmentRAG Architecture Explained: How Retrieval-Augmented Generation Works in 2026
A deep dive into RAG architecture, from naive RAG to advanced production pipelines. Covers chunking strategies, embedding models, retrieval methods, re-ranking, evaluation, and cost optimization.
15 min read
AI DevelopmentSelf-Hosted LLMs: How to Run Llama, Mistral & Open-Source Models On-Premise
A practical guide to self-hosting open-source LLMs. Covers hardware requirements, deployment frameworks like Ollama and vLLM, model selection, fine-tuning, and cost comparison vs API providers.
17 min read
AI DevelopmentVector Database Comparison 2026: Pinecone vs Weaviate vs Qdrant vs pgvector
An in-depth comparison of the top vector databases in 2026. Covers Pinecone, Weaviate, Qdrant, and pgvector across pricing, performance, features, hosting options, and use cases.
14 min read
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Asad Ali leads engineering at ZTABS. We ship AI agents, SaaS platforms, web, and mobile apps for 300+ clients. Tell us about your project — first call is free.