concept

application programming interface

Also known as: API

Facts (10)

Sources

10 RAG examples and use cases from real companies - Evidently AI evidentlyai.com Evidently AI Feb 13, 2025 4 facts

procedureTo respond to student questions, ChatLTV provides the LLM with the user query and relevant context retrieved from a vector database, with content chunks served via OpenAI's API.

referenceGrab's Report Summarizer integrates two in-house platforms: Data-Arks, a Python-based API platform housing frequently used SQL queries and Python functions, and Spellvault, an internal platform for storing, sharing, and refining LLM prompts.

claimGrab's A* bot is an AI-powered assistant that streamlines fraud investigations by using a collection of frequently used queries packaged as Data-Arks APIs.

procedureThe process for Grab's Report Summarizer involves triggering a report by calling a Data-Arks API to retrieve data, processing that data through Spellvault to generate a summary using an LLM, and delivering the final report via Slack.

Enterprise AI Requires the Fusion of LLM and Knowledge Graph stardog.com Stardog Dec 4, 2024 2 facts

referenceStardog Voicebox supports any database, document, or API, including structured, semi-structured, and unstructured data.

referenceSafety RAG supports any database, document, or API, including structured, semi-structured, and unstructured data.

bureado/awesome-software-supply-chain-security - GitHub github.com GitHub 1 fact

claimThe toolswatch/vFeed tool provides a correlated CVE vulnerability and threat intelligence database API.

Open-source license - Wikipedia en.wikipedia.org Wikipedia 1 fact

claimIn a 2021 case, the US Supreme Court permitted the recreation of an application programming interface (API) in a transformative product under the doctrine of fair use.

Weekly Innovations and Future Trends in Open Source dev.to Vitali Sorenko · DEV Community May 19, 2025 1 fact

measurementThe TensorFlow 3.5 upgrade improves distributed training efficiency by 20% and simplifies model deployment through API enhancements.

LLM Observability: How to Monitor AI When It Thinks in Tokens | TTMS ttms.com TTMS Feb 10, 2026 1 fact

claimDeploying large language models via API incurs costs per generated token and costs associated with mistakes, such as increased support time and customer churn.