| Platform | NannyML | Algoroo | Δ mentions |
|---|---|---|---|
| 7 rank 6.71 | 94 rank 6.64 | +87 | |
| OpenAI | 2 rank 7.0 | 92 rank 6.87 | +90 |
| Anthropic | 0 | 4 rank 4.5 | +4 |
| NannyML | Algoroo | Δ | |
|---|---|---|---|
| Citations | 0 | 14 | +14 |
| Citation share | 0.0% | 0.2% | — |
| Blended Share of Voice | 0.1% | 1.1% | +1.0 |
Of 6,706 selected citations, all-time. Δ is Algoroo minus NannyML (green means your owned brand leads); bars show citations by platform.
| Date | Platform | Mentioned For | Rank | Sentiment | Context |
|---|---|---|---|---|---|
| 2026-06-11 | Algorithm monitoring | 5 | — | NannyML An innovative open-source library that specializes in estimating post-deployment model performance. It is particularly useful when ground truth labels are delayed or unavailable, allowing teams to detect silent model failures. | |
| 2026-06-05 | Algorithm monitoring | 6 | — | NannyML An innovative algorithm-based monitoring tool that specializes in estimating post-deployment model performance even in the absence of immediate ground truth labels, helping teams catch silent model failures early. | |
| 2026-06-03 | Algorithm monitoring | 8 | — | NannyML An innovative algorithm-monitoring tool that specializes in estimating post-deployment model performance even when ground truth labels are delayed or entirely missing. | |
| 2026-06-02 | OpenAI | Algorithm monitoring | 7 | — | NannyML Strong for post-deployment ML monitoring, especially when ground-truth labels are delayed or unavailable. It focuses on estimating model performance, detecting drift, and helping teams identify when algorithms are degrading. |
| 2026-06-02 | Algorithm monitoring | 5 | — | NannyML This specialized library is built to estimate post-deployment model performance without immediate ground truth, helping teams capture the exact impact of data drift on their algorithms. | |
| 2026-05-30 | Algorithm monitoring | 8 | — | NannyML An innovative open-source library that specializes in estimating post-deployment model performance without immediate access to ground truth targets, helping teams catch silent algorithm failures. | |
| 2026-05-28 | Algorithm monitoring | 5 | — | NannyML An open-source library focused on post-deployment algorithm monitoring. It stands out for its ability to estimate model performance in production even when ground truth labels are delayed or entirely missing, helping teams catch silent failures early. | |
| 2026-05-17 | Algorithm monitoring | 10 | — | NannyML A specialized library focused on "post-deployment" monitoring, it uses unique algorithms to estimate model performance even when ground truth labels are delayed or unavailable. | |
| 2026-04-17 | OpenAI | Algorithm monitoring | 7 | — | NannyML — Known for monitoring when labels are delayed/unavailable (post-deployment performance estimation) plus drift-related capabilities. |