VectorFlow
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Vector Embedding Pipeline

We provide robust, scalable, and secure vector embedding services for AI companies. Focus on your core business logic and let us handle the data ingestion.

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Vector Embeddings as a Service

Simple API to Raw Embed Data

Embed Raw Data From Any Source.
Our technology-agnostic system can embed large volumes of data from any type of source.
No Infrastructure Worries.
Don't worry about setting up complex infrastructure. We provide an easy-to-use infrastructure as a self-hosted service and a managed service.
Out-of-the-box Highly Performant.
The embedding process can be easily parallelized and scaled to handle large volumes of data quickly. It retries automatically to ensure all your data is always embedded.
app.py
import requests

INTERNAL_API_KEY = "your_api_key_here"

url = "http://localhost:8000/embed"
headers = {
  "Content-Type": "multipart/form-data",
  "VectorFlowKey": INTERNAL_API_KEY
}

data = {
  'EmbeddingsMetadata': '{
    "embeddings_type": "open_ai", 
    "chunk_size": 256, 
    "chunk_overlap": 128}',
  'VectorDBMetadata': '{
    "vector_db_type": "pinecone", 
    "index_name": "test", 
    "environment": "us-east-1-aws"}'
}

files = {
  'SourceData': (
    'test_text.txt', 
    open('./src/api/tests/fixtures/test_text.txt', 'rb')
    )
}

response = requests.post(
  url, 
  headers=headers, 
  data=data, 
  files=files)

print(response.text)

Explore Different Use Cases

Semantic search.
Semantic search harnesses vector databases and embeddings to delve beyond mere keywords, understanding the context and intent behind queries.
Long-term LLM Memory.
Long-term LLM Memory utilizes vector embeddings and databases to store and recall vast amounts of information efficiently.
Question Answering.
Question Answering leverages vector embeddings and databases to comprehend and retrieve precise answers from vast datasets.
Automatic classification.
Utilize vector embeddings for automatic classification, harnessing their capability to understand and categorize data.
Recommendation System.
Leverage vector databases and embeddings to analyze and match user preferences with relevant content or products.
Cache LLM queries and responses.
Cache LLM queries and responses to enhance retrieval speed and optimize system performance.
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Chatbot for Customer Support
Businesses looking to enhance their customer support can utilize our product to create chatbots. These chatbots, powered by vector databases and embeddings, can understand and respond to customer queries with a depth of understanding that goes beyond mere keyword matching, offering more relevant solutions.
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In-house Knowledge Base for Employees
Companies can set up an in-house knowledge base for their internal teams using our product. This ensures that employees can quickly find and access company-specific information, policies, or procedures, with the system understanding the context behind each query, thanks to vector embeddings.
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Comprehensive Document Analysis
Organizations dealing with extensive documents, whether legal, technical, or research-based, can utilize our product for in-depth analysis. Vector embeddings capture the intricate details and contexts within the text, streamlining the process of extracting key insights and information.

Built for Developers

We built the easiest to use and most robust embedding engine for your AI applications.

Performance

Optimized for High Throughput

Engineered to handle high data throughput, ensuring your AI models receive the necessary information swiftly with low latency.

Built for Speed

With built-in parallelization, our service is designed to transform your data at high speed, accelerating your AI development process.

Designed for Massive Volume

Handle massive volumes of data, making it an ideal solution for AI applications that require extensive data ingestion and transformation.

Robustness

Built-in reliability and availability

VectorFlow is designed with built-in retry capabilities, ensuring that your data transformation processes are resilient and can recover from any interruptions.

Designed with Enterprises in Mind

Our service is built to meet the demanding needs of enterprises, providing a robust and reliable solution for your AI data pipelines.

Built on Scalable Infrastructure

Built on a scalable infrastructure that can grow with your needs, ensuring that you can handle increasing data volumes as your business expands.

Private, Secure, and Simple to Use

Secure in your Cloud

Hosting VectorFlow in your cloud for unparalleled control and security. You maintain complete data sovereignty, ensuring that your sensitive information remains exclusively within your boundaries.

Simple API Calls

We hide all the complexity behind simple API calls, making it easy for your team to use our service without needing extensive technical knowledge.

Managed Service

As a fully hosted solution, we eliminate the need for you to manage servers or deal with hosting issues, providing you with a hassle-free experience.

Get Started Right Now

Open Source Version

Self-host the vector embedding pipeline on your own infrastructure with our docker image.

Managed Service: Scale Without The Hassle

Ingesting, processing and storing data in vector databases at scale is hard. We take care of the underlying cloud infrastructure so you can focus on building your product.

Vector Embedding as a Service

Leave the Embeddings to Us

Stop wasting time on data ingestion pipelines and infrastructure management. Let us build scalable and robust pipelines for you. Focus on your core AI applications and leave the complexities of data transformation to us.