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Tangent AI
Instant predictive models and anomaly detection on time-series data.
What it does
- Instantly builds robust time-series predictive models and anomaly detection engines on complex datasets. - Automates feature engineering and selection processes to reduce data science overhead. - Integrates smoothly with major cloud data pipelines like Snowflake, Databricks, and Azure. - Delivers accurate forecasting for energy consumption, cloud spend optimization, and raw material pricing.
Why it works
Automates time-consuming model tuning and repetitive feature engineering to accelerate time-to-market. Provides hyper-automated time-series algorithms that adapt instantly to frequent underlying data changes. Offers flexible cloud connectors for fast deployment across existing data infrastructure pipelines. Delivers lightweight, scalable predictions that optimize heavy enterprise operational resources.
Category: AI & Automation
Team Size: 26-100
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As of 2026
AI & Automation
Revenue: $1M-$10M ARR
Instant predictive models and anomaly detection on time-series data.
Overview
Tangent AI is an advanced predictive modeling and time-series forecasting platform designed to help enterprises turn data into actionable insights. The software automates complex feature engineering and model training, allowing data science teams to deploy predictive pipelines in minutes instead of weeks. By providing lightweight automation and seamless cloud data warehouse integrations, it optimizes resource allocation across energy, finance, and cloud operations. Organizations rely on Tangent to eliminate manual bottlenecks and scale predictive analytics effortlessly.
Founded year: 2014
Team size: 26-100
HQ: Belgium
Funding status: Funded
Revenue source: Subscriptions
Customer type: B2B
Pricing: Subscription
Tech stack: Time-Series AI Engine, Automated Feature Engineering, Cloud APIs
Platform: Web • Cloud
Integrations: Microsoft Azure, Databricks, Snowflake, AWS, Custom APIs
Founder story
Tangent Works was established to solve the complexity and latency bottlenecks inherent in traditional predictive modeling. Headquartered internationally, the company developed an automated time-series engine designed to instantly build and operationalize accurate AI models. It serves enterprise customers worldwide seeking scalable forecasting solutions.
What it does
- - Instantly builds robust time-series predictive models and anomaly detection engines on complex datasets
- - Automates feature engineering and selection processes to reduce data science overhead
- - Integrates smoothly with major cloud data pipelines like Snowflake, Databricks, and Azure
- - Delivers accurate forecasting for energy consumption, cloud spend optimization, and raw material pricing.
Who it's for
- Data Scientists
- Cloud Engineers
- Energy Trading Teams
- Enterprise Analytics Leaders
Why it works
- Automates time-consuming model tuning and repetitive feature engineering to accelerate time-to-market
- Provides hyper-automated time-series algorithms that adapt instantly to frequent underlying data changes
- Offers flexible cloud connectors for fast deployment across existing data infrastructure pipelines
- Delivers lightweight, scalable predictions that optimize heavy enterprise operational resources.
Growth strategies
- Expanding enterprise connectors for modern cloud data warehouses and lakes
- Targeting high- stakes vertical markets such as smart grids, utilities, and cloud financial governance
- Scaling self- service onboarding for data science teams seeking automated copilot workflows
- Enhancing multi- variable time-series capabilities for global supply chain optimization
Alternatives
Comparison overview
- Traditional AutoML platforms require extensive manual pipeline construction and data tuning, whereas Tangent AI instantly generates automated time-series models in minutes.
- Standard business intelligence tools focus strictly on historical data visualization, while Tangent specializes in proactive predictive forecasting and anomaly detection.