Cloudglue: Video/Audio to Structured, LLM-Ready Data

Cloudglue converts video/audio into clean, structured, LLM-ready data—powering smarter AI workflows in seconds.

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Cloudglue: Video/Audio to Structured, LLM-Ready Data
Directory : AI Video Search, Large Language Models LLMs, AI API, AI Video Summarizer, AI Transcription

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What is Cloudglue?

Cloudglue is a purpose-built infrastructure layer that converts raw video and audio streams into clean, structured, and semantically rich data — engineered from the ground up for large language models and AI agents. It unlocks the latent intelligence in your multimedia assets: transforming hours of meeting footage, training videos, or customer calls into queryable JSON, timestamped summaries, speaker-aware transcripts, and multimodal embeddings — all via simple, scalable APIs.

How to use Cloudglue?

Integrate Cloudglue in minutes — not weeks. Choose your path: deploy a single `POST /v1/query` call for instant, managed video Q&A (no RAG pipelines required), or leverage fine-grained endpoints like `/extract`, `/summarize`, and `/embed` to build custom workflows. Whether you're indexing 10 videos or 10,000, Cloudglue handles ingestion, processing, and output formatting — so your team focuses on building AI, not preprocessing media.

Cloudglue's Core Features

Built for video — not bolted onto it

One-click AI enablement: go from upload to answer in seconds

Blazing speed: 50 minutes of video → fully structured, LLM-ready output in under 3 minutes

Adaptive fidelity: dial in precision — from verbatim transcripts to scene-level insights, speaker intent, and visual-audio correlations

Domain-agnostic indexing: works natively with sales calls, engineering demos, compliance trainings, and more

Enterprise-grade reliability: SOC 2-aligned, scalable concurrency, and zero-config fault tolerance

Y Combinator-backed — shipping real infrastructure for real AI teams

Cloudglue's Use Cases

Power knowledge graphs with temporal, multimodal video context

Surface cross-video trends — e.g., “What objections arise most frequently in Q3 sales demos?”

Fuel conversational AI with accurate, citation-aware answers about video content

Implement lightning-fast semantic search across petabytes of archived video

FAQ from Cloudglue

What does Cloudglue do?

How fast is Cloudglue?

What kind of control does Cloudglue offer over data extraction?

Is Cloudglue suitable for enterprise use?

How are API Credits consumed?

FAQ from Cloudglue

What is Cloudglue?

Cloudglue is an API-native platform that ingests video and audio files and outputs structured, model-ready data — including time-aligned transcripts, speaker diarization, keyframe descriptions, topic clusters, and vector embeddings — all optimized for consumption by LLMs, retrieval systems, and autonomous agents.

How to use Cloudglue?

Developers integrate Cloudglue using RESTful APIs. Start with `POST /v1/query` for immediate video Q&A, or compose modular pipelines using dedicated endpoints for transcription, summarization, entity extraction, and multimodal embedding — all with consistent authentication and error handling.

What does Cloudglue do?

It eliminates the video-to-data bottleneck: converting unstructured multimedia into standardized, machine-actionable formats — enabling AI applications to interpret, search, reason over, and respond to video content as naturally as they do text.

How fast is Cloudglue?

Processing scales linearly and predictably: a 50-minute video yields complete, structured output — including embeddings and metadata — in ≤3 minutes. Latency remains sub-second for queries on indexed libraries, regardless of scale.

What kind of control does Cloudglue offer over data extraction?

Full spectrum control — from lightweight `transcribe_only` mode (fast, low-cost) to `multimodal_deep` (visual + audio + contextual analysis). You define granularity per use case: segment duration, speaker resolution, confidence thresholds, and output schema.

Is Cloudglue suitable for enterprise use?

Absolutely. Cloudglue supports SSO, audit logging, private VPC deployment options, SLA-backed uptime, and compliance-ready architecture — trusted by fast-growing AI teams building mission-critical video intelligence products.

How are API Credits consumed?

Credits are deducted per successful request, based on media duration and selected feature tier. For example: `transcribe` uses 2 credits/minute; `extract` (with speaker + summary + entities) uses 6 credits/minute; `embed` consumes 4 credits/minute. Unused credits roll over monthly.