AI Engineering
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LLM Evaluation Frameworks: Proving Your AI Feature Actually Works
"It seems good" does not survive procurement. Eval set construction, judge models, regression gating, and the metrics that hold up in an enterprise deal.
Gaurang Ghinaiya
July 31, 2026
AI Document Processing: OCR + LLM Extraction Pipelines That Hold Up
Invoices, intake forms, contracts: document extraction is now an LLM pipeline problem. Architecture, confidence thresholds, and the review queue design.
Gaurang Ghinaiya
July 30, 2026
LLM Cost Optimization in Production: Token Economics for Real Products
LLM bills grow faster than usage because context grows. Prompt caching, model routing, context budgets, and the attribution you need before optimizing.
Gaurang Ghinaiya
July 29, 2026
AI Agents for Business Automation: What Works Beyond the Demo
Agents are LLMs with permission to act. Where they beat RPA, how to design tools they cannot misuse, and the guardrails that make them deployable.
Gaurang Ghinaiya
July 28, 2026
Production RAG Architecture: Chunking, Embeddings, Hybrid Retrieval, and Anti-Hallucination. The Complete Guide
RAG is not a single thing. It is a pipeline with seven or eight discrete engineering decisions, each of which significantly affects accuracy. This is the complete architecture guide based on what we have learned shipping RAG systems to production.
Gaurang Ghinaiya
June 3, 2026
LLM Integration Patterns for B2B SaaS: From API Wrapper to Production-Grade AI Feature
Adding an LLM to your B2B product is not the same as building a consumer chatbot. Token costs, reliability, latency, multi-tenant data isolation, and auditability all look different when your customers are businesses using your AI feature in production workflows every day
Gaurang Ghinaiya
May 28, 2026
The Anti-Hallucination Stack: Engineering LLM Products That Are Accurate Enough to Trust
Hallucination is not a bug you fix. It is a property of the model that you design around. The engineering work involves building detection layers, confidence mechanisms, and fallback behaviors that make a product trustworthy, even when the model is wrong.
Gaurang Ghinaiya
May 4, 2026
Multi-Tenant SaaS Architecture: Isolation Models, Data Strategies, and the Decisions That Scale
The multi-tenancy architecture decision you make when you have 10 customers is the architecture you will live with when you have 10,000. This is the tradeoff analysis for each isolation model and the implementation patterns that hold up at scale.
Gaurang Ghinaiya
April 8, 2026
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