Time Series Inventory Forecasting
ikigailabs.ioInventory Forecasting produces inventory projections up to 30 months into the future by analyzing historical inventory data. It relies on ensemble machine learning techniques combined with automated model selection to determine how best to model the data.
By leveraging multiple models in an ensemble, this solution is designed to deliver more stable and accurate forecasting outcomes. The automated model selection capability evaluates the input data and selects the most suitable model configuration to generate the forecasts.
LLM mention score The LLM mention score is the total number of mentions of this brand in different LLM chatbots, normalized to the scale from 0 to 100. You can get actual, non-normalized numbers via the LLM Mention API from DataForSEO.
Normalized 0–100 · last 8 weeks
DataForSeo API
Get LLM mention data of any company via DataForSEO API
Get access to the structured data on keyword, brand, and website mentions in LLMs, including metrics like AI search volume, impressions, and mentions count.
How to get LLM mention data →// Fetch Time Series Inventory Forecasting mention score POST /v3/content_analysis/summary { "keyword": "Time Series Inventory Forecasting", "type": "llm_mentions", "date_from": "2025-01-01" }
