The LayBuild blog
How AI support agents work, and where they break
We build an AI agent that answers support questions from your own documents, says so when they don't cover the question, and lets your team take over the chat. These posts explain how that works, where it falls short, and how to measure it honestly.
1 to 7 of 7 articles

Retrieval and grounding
Multilingual AI Customer Support: Cross-Language RAG, Embeddings & Global Scale
Multilingual AI customer support: why LayBuild retrieval is English-first, what multilingual embeddings change, and how to plan handoffs for other languages.
9 min read

Retrieval and grounding
Parent-child chunking for RAG: choosing a chunk size
How LayBuild splits documents into parent and child chunks for RAG: heading-aware splitting, chunk sizes, token overlap, and what each choice costs.
8 min read

Retrieval and grounding
Sparse and Dense Retrieval: BM25 vs Vector Search Benchmarks for RAG
How to benchmark sparse, dense and hybrid retrieval on your own support documents, using recall@k and MRR, and how to test it on LayBuild.
8 min read

Retrieval and grounding
Fine-tuning or retrieval for support bots: a decision guide
When fine-tuning a model helps customer support, when retrieval is the better tool, and why LayBuild uses retrieval and does not fine-tune.
6 min read

Retrieval and grounding
SaaS knowledge base optimization for AI support & RAG (2026)
How to write a SaaS knowledge base an AI support agent can retrieve from: one question per heading, answer first, customers' words and a monthly review.
8 min read

Retrieval and grounding
pgvector Hybrid Search: PostgreSQL, RRF & Vector RAG
pgvector hybrid search in PostgreSQL: vector and full-text results merged with Reciprocal Rank Fusion, parent-child chunks and a 0.4 relevance floor.
10 min read

Retrieval and grounding
How LayBuild limits made-up answers, and where it fails
Strict knowledge-base mode, the no-retrieval short circuit, the 25% stemmed-overlap check and auto-learning: what each catches and what gets through.
7 min read