docs: add base_model field + tamz.ai backlinks

README.md

@@ -3,6 +3,7 @@ language:
 - pt
 license: apache-2.0
 library_name: sentence-transformers
+base_model: ibm-granite/granite-embedding-97m-multilingual-r2
 tags:
 - sentence-transformers
 - feature-extraction
@@ -53,6 +54,8 @@ model-index:
 
 Fine-tuned from [`ibm-granite/granite-embedding-97m-multilingual-r2`](https://huggingface.co/ibm-granite/granite-embedding-97m-multilingual-r2) using a **Karpathy-style autoresearch loop** — 36 autonomous training iterations on an RTX 5090, each proposing and self-validating its own strategy. **35 out of 36 iterations improved the model (97% acceptance rate).**
 
+Built at [**TAMZ**](https://tamz.ai) — a Brazilian B2B sales intelligence platform that identifies, enriches, and delivers company leads ready for outreach. The training data comes directly from TAMZ's enrichment pipeline over 32M Brazilian companies from the Receita Federal.
+
 ---
 
 ## MTEB Benchmark Results (PT-BR)
@@ -186,7 +189,7 @@ embeddings = model.encode(texts, truncate_dim=128)
 ## Best For
 
 ✅ Semantic search over Brazilian business data  
-✅ B2B lead discovery and company matching  
+✅ B2B lead discovery and company matching (e.g. [TAMZ](https://tamz.ai))
 ✅ Company similarity, clustering, deduplication  
 ✅ PT-BR RAG pipelines with business documents  
 ✅ Memory systems for Portuguese AI agents  
@@ -222,6 +225,7 @@ Apache 2.0 — same as the base IBM Granite Embedding model.
   publisher = {HuggingFace},
   url       = {https://huggingface.co/calneymgp/braza-embedding-ptbr-v1},
   note      = {Fine-tuned from IBM Granite 97M on 474K Brazilian B2B companies
-               using 36-iteration autonomous training loop (RTX 5090)}
+               using 36-iteration autonomous training loop (RTX 5090).
+               Built at TAMZ (https://tamz.ai)}
 }
 ```