> For the complete documentation index, see [llms.txt](https://docs.pending.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.pending.ai/getting-started/demo.md).

# Demo

Click here to open and try the demo now:

{% embed url="<https://colab.research.google.com/drive/14WMqrI5gepcgQyXN63nmm0h4vWMFJCkz#scrollTo=422c2d56>" %}

**Pending AI Demo Notebook** — An end-to-end walkthrough of the Pending AI platform in Google Colab, covering:

1. **Molecule Generation** — sample novel molecules from Pending AI's generative models, with lightweight post-filtering on Lipinski's Rule of 5.
2. **Similarity Search** — build an in-memory `usearch` index over Morgan fingerprints and run a Tanimoto similarity search against a reference compound (Imatinib).
3. **Property Analysis** — visualize QED, cLogP, and molecular weight distributions across the generated set, with a target molecule overlaid for comparison.
4. **Diversity Analysis** — assess sample diversity via pairwise property-distance distributions.
5. **Synthesizability Screening** — submit single and batch jobs to the Retrosynthesis Prediction service, poll for completion, and export/download interactive HTML reports depicting the resulting synthetic routes.
6. **TwinOracle** — try Pending AI's next-generation retrosynthesis engine, including a tunable full-parameter example (search depth, time budget, building-block cost/lead-time/region constraints).

Requires a registered Pending AI account (the notebook walks through login via the `pendingai` Python package) — [reach out here](https://pending.ai/#contact) to trial the platform.