Nixtla

Nixtla is a time series intelligence company that develops forecasting and anomaly detection tools for data teams and enterprises. Its product line spans the open-source Nixtlaverse libraries — StatsForecast (statistical and econometric models), NeuralForecast (neural forecasting algorithms), MLForecast (scalable machine learning), HierarchicalForecast (probabilistic hierarchical forecasting), plus DatasetsForecast, UtilsForecast and CoreForecast utilities — and a commercial enterprise platform built around TimeGPT, described as a foundation model for time series forecasting.

The commercial product, marketed as the Nixtla Engine, is organized as an ingestion layer connecting to warehouses, lakehouses, object storage, dataframe libraries and spreadsheets (Databricks, Snowflake, S3/GCS/ADLS, Pandas/Polars/Spark, Excel/CSV); an engine layer exposing over 200 forecasting models through a Python package or API and supporting multivariate forecasting, real-time anomaly detection, driver-based explainability and what-if scenario planning; and a consumption layer that delivers predictions and alerts into notebooks, BI dashboards (Tableau, Power BI, Looker), embedded applications via REST, and Slack or Teams. Security and governance features listed include SSO, RBAC, audit logging, SOC 2 Type II, and VPC/BYOC deployment. Releases cited around the 2026 Series A include TimeGPT 2.1 and Nixtla Enterprise 2.0, which added multivariate modeling and agentic forecasting.

Stated use cases include demand planning, inventory management, energy and power demand forecasting, energy price prediction, battery dispatch optimization, logistics, financial indicators, user engagement, asset prices and equipment anomaly detection.

Founding story

Nixtla was founded by Max Mergenthaler Canseco (Chief Executive Officer) and Cristian Challu (Chief Scientific Officer), longtime collaborators who met while studying engineering in Mexico. Both founders have technical backgrounds in machine learning and time series analysis spanning academic research, consulting and applied deployment. The company was created to reduce the cost and operational burden of building and maintaining time series forecasting systems at scale, which typically require specialized data science teams to clean historical data and test many statistical and machine learning models.

Business model

Nixtla combines freely available open-source forecasting libraries with a commercial enterprise platform sold to organizations, offered as API-based deployments or self-hosted/on-premises implementations so customers can retain control of sensitive data. The open-source ecosystem functions as the distribution and adoption channel for the paid enterprise product.

Revenue comes from the commercial enterprise offering built on TimeGPT and the Nixtla Engine, available through cloud/API access or self-hosted and VPC/BYOC deployments; the underlying Nixtlaverse libraries remain open source.

Traction

The open-source ecosystem is reported at 75 million downloads and 17,000 GitHub stars on the company website, with 45 million downloads and more than 15,000 stars cited in February 2026 Series A coverage. Named enterprise customers include Microsoft, Prudential, Unilever, Decathlon, o9, Zalando, Lyft and public-sector organization IMSS. Reported customer outcomes include an 85% reduction in forecasting false alerts at a mobility company (Lyft), a 35% increase in store-level forecast accuracy at a retail brand, sub-five-second TimeGPT-1 deployments at Microsoft, and pipeline-level results such as more than 500,000 forecasts and 22,000+ daily forecasts for individual customers.

Latest developments

In February 2026 Nixtla announced a $16 million Series A led by Energize Capital with participation from True Ventures and GreatPoint Ventures, with Energize partner Juan Muldoon joining the board and senior associate Agustina Soriano Sergi joining as board observer. The company said proceeds will strengthen and scale its production-grade models across enterprise and open-source offerings and fund hiring across engineering, product and sales. Recent product releases cited include TimeGPT 2.1 and Nixtla Enterprise 2.0, adding multivariate modeling and agentic forecasting.