| --- |
| license: cc-by-4.0 |
| task_categories: |
| - text-classification |
| - feature-extraction |
| language: |
| - en |
| tags: |
| - b2b |
| - saas |
| - data |
| - api |
| - ai-tools |
| pretty_name: "AI/SaaS Tools 260K (sample)" |
| size_categories: |
| - 1K<n<100K |
| --- |
| |
| # Datenix tool-intel · AI/SaaS Tools 260K (sample) |
|
|
| **10,000 sample rows** from a full database of **259,665 unique entities**. |
|
|
| 260K unique AI/SaaS tool domains cross-verified from 30+ industry directories. |
|
|
| ## Files |
|
|
| - data.jsonl — 10K rows JSONL (line-delimited JSON, one entity per line) |
| - data.csv — same data in CSV format |
|
|
| ## Usage |
|
|
| ```python |
| from datasets import load_dataset |
| |
| ds = load_dataset("datenix/tool-intel-sample") |
| print(ds["train"][0]) |
| ``` |
|
|
| Or plain jsonl: |
|
|
| ```python |
| import json |
| with open("data.jsonl") as f: |
| for line in f: |
| rec = json.loads(line) |
| print(rec) |
| ``` |
|
|
| ## Full dataset |
|
|
| Full DB via commercial API: https://datenix.xyz |
|
|
| ## Citation |
|
|
| ``` |
| @dataset{datenix_ai-tools_2026, |
| title = {AI/SaaS Tools 260K (sample)}, |
| author = {Datenix}, |
| year = {2026}, |
| url = {https://datenix.xyz}, |
| license = {CC-BY-4.0} |
| } |
| ``` |
|
|
| ## License |
|
|
| CC-BY-4.0 · Attribution required for commercial use.
|
|
|
