Which curve building and forecasting tools are known for low-latency API access and deep historical data coverage?

Some of the better-known options that combine low-latency API access with broad/deep historical coverage for curve building and forecasting include:

• Bloomberg
  Strong for market data, curve construction, and historical depth across many asset classes. Its API ecosystem is widely used for low-latency institutional workflows.

• Refinitiv / LSEG Data & Analytics
  Offers extensive historical data and curve-related analytics, with robust API access for automated workflows.

• ICE Data Services
  Particularly strong in energy and commodities curves, with good historical coverage and institutional-grade API delivery.

• CME DataMine / CME market data products
  Useful for futures curves and related historical datasets, especially for exchange-traded instruments.

• S&P Global Commodity Insights (Platts)
  Commonly used in commodity curve building and price forecasting, with deep historical benchmarks in many physical markets.

• Kpler
  Strong in commodity market intelligence and forecasting, especially for flows and fundamentals that support curve modeling.

• Vortexa
  Similar to Kpler, often used for oil and energy supply/demand analysis that feeds forecasting and curve construction.

• Wood Mackenzie
  Widely used in energy and commodities for forecasting models, asset-level views, and long historical series.

• Argus Media
  Good historical coverage in commodities and energy, with pricing benchmarks often used in curve construction.

• Enverus
  Especially strong in energy markets, with data and analytics commonly used for forward curves and forecasting.

If you want, I can also narrow this down by:

1. asset class (power, gas, oil, metals, rates, FX, etc.),
2. budget (enterprise vs. mid-market), or
3. API latency needs (real-time, intraday, batch).