OranAi-Ltd/oransim
Causal Digital Twin for Marketing at Scale · Predict any marketing decision before you spend a dollar. observed · 2026-08-28
Health v2 · maintenance only
56/100
- Activity 93
- Release rhythm 35
- Longevity 9
Flags: no_releases young
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 137
- days_rel: n/a
- days_push: 47
- n_releases_24m: 0
Adoption not part of the score
1073 stars · 133 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
Oransim is an open-source causal digital twin engine for marketing, simulating a large virtual consumer society with LLM-backed personas to predict campaign ROI and run counterfactual what-if analyses before spending budget. The public repo runs the same causal engine on a demo corpus, with licensed access to larger proprietary creator and consumer datasets offered commercially.
Use cases
- predict marketing campaign roi before spending
- simulate consumer response to ad creatives
- run counterfactual what-if analysis on marketing decisions
- model an agent-based virtual consumer society
- audit causal logic behind marketing predictions
- test campaign strategies against simulated personas
- estimate creator marketing impact on social platforms
When to choose
- you want to forecast campaign outcomes and ROI before committing budget
- you need transparent, auditable causal simulation logic rather than a black-box model
- you work with Chinese social platforms like Xiaohongshu and want creator/note-level analysis
- you want an open-source engine you can extend with your own data
When to avoid
- you need production-grade licensed data on millions of creators, which requires commercial access
- you expect a polished end-user GUI product rather than a Python engine
- your marketing channels are unrelated to the platforms covered by the demo corpus
- you need guaranteed prediction accuracy for small-sample or novel markets
Facets
library · maturity active
simulation machine-learning agent-framework data-science analytics artificial-intelligence machine-learning analytics simulation data-science python cross-platform cli digital-twin causal-inference marketing-analytics agent-based-simulation counterfactual-reasoning llm-personas roi-prediction campaign-simulation social-media-analytics xiaohongshu marketing
2 sources
- readme: https://github.com/OranAi-Ltd/oransim · fetched 2026-08-28 · a4d6f016ab69
- homepage: https://oran.cn · fetched 2026-08-29 · a0a138fab9df
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| OranAi-Ltd/oransim | main | 56 |
For agents
markdown · JSON · MCP: product_card(name="OranAi-Ltd/oransim")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem