FAIM: Time-Series Forecasting API
Serverless inference for foundation time-series models
# Developer ToolsWhat is FAIM: Time-Series Forecasting API ?
FAIM (Foundation AI Models) is a platform for serverless inference of foundation time-series models. It lets you generate forecasts instantly — no setup or infrastructure needed. We built FAIM because the lack of accessible infrastructure for foundation time-series models slows down their adoption in industry. Try it out: 1️⃣ Register to get your API key → https://faim.it.com 2️⃣ Run forecasts via our Python SDK → https://github.com/S-FM/faim-python-client
Problem
Users need to set up and manage their own infrastructure for deploying time-series foundation models, which requires significant technical expertise and time investment, slowing adoption in industry.
Solution
A serverless inference platform for foundation time-series models, allowing users to generate forecasts instantly via API and Python SDK without infrastructure setup.
Customers
Data scientists, ML engineers, and analytics teams in industries like finance, retail, and supply chain.
Unique Features
Instant access to pre-trained time-series models, serverless architecture eliminating infrastructure management, and Python SDK for seamless integration.
User Comments
Simplifies time-series forecasting workflow
Reduces deployment time from weeks to minutes
API documentation is clear and intuitive
Useful for rapid prototyping
Lacks customization options for advanced users
Traction
Python SDK launched (GitHub repository), API key registration available, traction metrics (MRR/users) not publicly disclosed.
Market Size
The global time-series analytics market is projected to reach $9.3 billion by 2023 (MarketsandMarkets report).
