Mixpeek for Backend Developers
Add multimodal search and intelligence to your application with a single API
Backend developers building applications that handle images, video, audio, or documents need search and classification capabilities without becoming ML infrastructure experts. Mixpeek provides REST APIs for ingestion, processing, and retrieval that integrate into any backend stack.
What's Broken Today
1ML infrastructure is not your job
You need to add video search or image classification to your app, but standing up GPU clusters, managing model versions, and building vector databases is a full-time role you do not have.
2Inconsistent API patterns across providers
Using one service for OCR, another for speech-to-text, and a third for embeddings means learning three different SDKs, auth patterns, and error handling conventions.
3Scaling processing with traffic
User uploads spike unpredictably. Your processing pipeline needs to handle 10x traffic bursts without dropping files or returning stale results.
4Complex query requirements
Product asks for search that combines text similarity with metadata filters and reranking. Building this from scratch on top of a vector database takes months.
How Mixpeek Helps
Unified REST API
One API for uploading, processing, searching, and classifying multimodal content. Consistent authentication, pagination, and error handling across all endpoints.
Async batch processing
Submit files for processing and poll batch status or set up webhooks. No need to manage queues, workers, or retry logic in your application code.
Multi-stage retrieval
Configure retrievers that chain vector search with attribute filters, reranking, and aggregation. Get production-quality search by defining stages, not writing search algorithms.
Namespace-based multi-tenancy
Each namespace maps to an isolated Qdrant collection. Serve multiple customers from a single Mixpeek deployment with strict data isolation at the storage layer.
How It Works for Backend Developers
Create a namespace and collection
Set up a namespace for your application (or one per tenant) and configure a collection with the extractors that match your content type (video, images, documents).
Upload files through the bucket API
Push user-uploaded content to a Mixpeek bucket via the REST API. Each upload tracks the source file and metadata for lineage.
Trigger processing and track batches
Start collection processing with a single POST request. Use the batch status endpoint to build progress indicators or webhook handlers in your application.
Query documents through retrievers
Execute retriever pipelines to search processed content. Results include relevance scores, metadata, and source references that your application can render directly.
Relevant Features
- REST API
- Batch processing
- Retrievers
- Namespaces
- Webhooks
Integrations
- S3
- REST API
- Python SDK
- Node.js
- PostgreSQL
"We added video search to our platform in a single sprint. The API handles all the ML complexity, and our backend team just integrates with REST endpoints like any other service."
Jordan Michaels
Senior Backend Developer, StreamStack
Frequently Asked Questions
Related Resources
Industry Solutions
Implementation Recipes
Semantic Multimodal Search
Unified semantic search across all content types. Query by natural language and retrieve relevant video clips, images, audio segments, and documents based on meaning-not keywords or manual tags.
Multimodal RAG
Retrieval-augmented generation across video, images, and text. Retrieve relevant multimodal context, then pass to your LLM with citations back to source timestamps and frames.
Hierarchical Classification
Assign content to multi-level category hierarchies using embedding-based classification. Define your taxonomy once, then classify new content automatically with confidence scores.
Get Started as a Backend Developer
See how Mixpeek can help backend developers build multimodal AI capabilities without the infrastructure overhead.