# Synthefy Docs

## Docs

- [Synthefy Agent is Online!](https://docs.synthefy.com/agent/overview.md)
- [Quickstart](https://docs.synthefy.com/agent/quickstart.md): Quickly access Synthefy's forecasting and enrichment capabilities through the Agent.
- [API Client](https://docs.synthefy.com/api-reference/SynthefyPythonLibrary/api-client.md): Synthefy API client for making forecasting requests
- [ForecastV2Request](https://docs.synthefy.com/api-reference/SynthefyPythonLibrary/forecast-v2-request.md): A request for forecasting and model specification
- [ForecastV2Response](https://docs.synthefy.com/api-reference/SynthefyPythonLibrary/forecast-v2-response.md): A response containing forecast results for multiple samples
- [SingleEvalSamplePayload](https://docs.synthefy.com/api-reference/SynthefyPythonLibrary/single-eval-sample-payload.md): A single payload for forecasting models
- [SingleSampleForecastPayload](https://docs.synthefy.com/api-reference/SynthefyPythonLibrary/single-sample-forecast-payload.md): A single sample forecast payload containing forecast results
- [Python SDK Reference](https://docs.synthefy.com/api-reference/python-sdk.md): Complete reference for the Synthefy Python SDK
- [Changelog](https://docs.synthefy.com/changelog.md): Latest updates and improvements to Synthefy
- [Cloud API Quick Start](https://docs.synthefy.com/forecasting-api/cloud-quickstart.md): Get started with Synthefy's Cloud Forecasting API using the simplest possible example.
- [Forecasting API](https://docs.synthefy.com/forecasting-api/overview.md): Direct access to Synthefy's foundation models for time series forecasting via REST API.
- [On-Prem Quick Start](https://docs.synthefy.com/forecasting-api/quickstart.md): Deploy the Forecasting API locally and make your first forecast request using the Python client.
- [Text-Guided Forecasting](https://docs.synthefy.com/forecasting-api/text-guided-forecasting.md): Combine textual context with time series data using Milano for scenario-aware forecasting.
- [Welcome to Synthefy](https://docs.synthefy.com/index.md): The foundational platform for time series forecasting and data synthesis
- [Data enrichment for forecasting](https://docs.synthefy.com/notebooks/data_enrichment.md): Learn how to enhance your datasets by integrating valuable insights from trusted external data sources, improving accuracy, depth, and decision-making potential.
- [Overview](https://docs.synthefy.com/sdk/overview.md): Synthefy Forecasting provides fast, accurate time-series forecasting with simple Python APIs.
- [Quickstart](https://docs.synthefy.com/sdk/quickstart.md)
- [Setting up your API key](https://docs.synthefy.com/setup/api_key.md): Quickly and securely connect to the Synthefy SDK by setting up your API key — in code or through environment variables.
- [How to use Synthefy Docker](https://docs.synthefy.com/setup/docker.md): This documentation walk you through how to use the docker for development and forecasting model inference.
- [Anomaly Detection](https://docs.synthefy.com/usecases/anomaly_detection.md): Learn how to detect anomalies in multivariate time series data using Synthefy's forecasting API with forecast-error based detection.
- [Covariate Importance](https://docs.synthefy.com/usecases/covariate_importance.md): Demonstrates tools for future leaked covariate importance in Synthefy Foundation Model using zero-perturbation analysis. Generate synthetic autoregressive time series with exogenous Fourier inputs (ARX) and estimate covariate importance without retraining using zero perturbation analysis.
- [Economic Indicator Backtesting](https://docs.synthefy.com/usecases/economic_backtesting.md): Learn how to forecast economic indicators using Synthefy's multi-variate forecasting with macroeconomic data from FRED and Haver.
- [Hotel Demand Forecasting](https://docs.synthefy.com/usecases/hotel_demand.md): Learn how to forecast hotel demand using Synthefy's multi-variate forecasting API.
- [Inventory Forecasting](https://docs.synthefy.com/usecases/inventory_forecasting.md): Learn how to improve inventory forecasting accuracy by incorporating weather data and how to do conditional forecasting to discover which items move together.
- [Pricing Simulation](https://docs.synthefy.com/usecases/pricing_simulation.md): Learn how to run pricing simulations using Synthefy's AI-powered conditional forecasting to optimize a pricing strategy and maximize revenue.

## OpenAPI Specs

- [openapi](https://docs.synthefy.com/api-reference/openapi.json)

## Optional

- [Website](https://synthefy.com)
- [GitHub](https://github.com/Synthefy)