Solutions

The fastest embeddings for search at scale

Rapidly process millions of data points using any embedding model.

Trusted by top engineering and machine learning teams
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Infrastructure built for performance and flexibility

Accelerate initial queries

With optimized cold starts and elastic autoscaling, you can rapidly process entire databases, serve bursts of requests, or scale down to zero to save on costs.

Use any embedding model

Ship custom Docker images, package any AI model using our open-source Python library, Truss, or use Baseten Chains for ultra-low-latency compound AI.

Customize your inference

At Baseten, you have full control over how you balance performance, cost, and accuracy. Our engineers are obsessed with meeting or exceeding your success criteria.

Any model, any application, custom inference

Semantic search

Get ultra-low-latency, high-quality search with any model series, including BAAI General Embedding (BGE), Stella, and SFR-Embedding models.

Recommender systems

Enable real-time RecSys experiences even during peak demand, with fluid autoscaling for any dataset size or traffic level.

Custom models

Deploy any open-source, closed-source, fine-tuned, or custom embedding model tailored to your use case and performance targets, including Nomic, NV-Embed, and Voyage model series.

Powering embeddings and search at massive scale

Production-grade reliability

Reliably serve customers anywhere in the world, any time, backed by our five 9's uptime and global deployment options.

Ship low-latency pipelines

Pass embeddings to any model or processing step, each equipped with custom hardware and autoscaling using Baseten Chains.

Auto-scale to peak load

Deliver fast response times under any load with rapid cold starts and elastic autoscaling.

Embeddings on Baseten

Build with Embeddings

Learn about the world’s fastest Embedding

Learn how our engineers optimized embedding models from the ground up for the lowest latency and highest throughput.

Read the blog

Learn how our engineers optimized embedding models from the ground up for the lowest latency and highest throughput.

Read the blog

Get the best models

See which open-source embedding models are best for building agents, RAG, and RecSys, and more.

Pick a model

See which open-source embedding models are best for building agents, RAG, and RecSys, and more.

Pick a model

Build flexible workflows

Integrate embedding models into multi-model compound AI workflows to power agentic memory.

Check out the docs

Integrate embedding models into multi-model compound AI workflows to power agentic memory.

Check out the docs

Sahaj Garg logoSahaj Garg, Co-Founder and CTO
Sahaj Garg logo

Sahaj Garg,

Co-Founder and CTO