Sold by: deepset GmbH
Deployed on AWS
The Haystack Enterprise Platform is an AI Orchestration solution for Gen AI applications and agents
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Overview
deepset takes an outcome-first approach to delivering mission-critical Gen AI solutions. Its AI Orchestration solution combines expert AI services with Haystack, driving fast time-to-value, continuous innovation, and seamless scalability. Enterprises like Airbus, OakNorth, YPulse, and The Economist rely on deepset to customize AI agents and applications across finance, sales, service, customer experience, and product development - reporting 5X ROI, 40% efficiency gains, and 99% accuracy. With deep AI expertise and production-grade technology, deepset solves complex business challenges with a model-agnostic, flexible approach to data, integrations, and deployments - so you can customize AI to work your way. For pricing and purchasing information, please inquire via the following contact form https://www.deepset.ai/contact-us
Highlights
- Build and scale AI apps fast - Use customizable templates, modular pipelines, and user feedback to iterate and deploy in the cloud or your VPC.
- Seamless model experimentation - Instantly swap between commercial and open-source LLMs with deepset's flexible AI pipeline.
- Enterprise-ready integrations - Connect directly with Amazon OpenSearch and Amazon Bedrock for high-performance search and foundation model access.
Details
Sold by
Delivery method
Deployed on AWS
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Pricing
Pricing is based on the duration and terms of your contract with the vendor. This entitles you to a specified quantity of use for the contract duration. If you choose not to renew or replace your contract before it ends, access to these entitlements will expire.
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Dimension | Description | Cost/12 months |
|---|---|---|
Haystack Enteprise Platform | Full access to Haystack Enteprise Platform. Multiple licensing options. | $100,000,000.00 |
Vendor refund policy
Refunds may be processed at our discretion. Please contact us at support@deepset.ai
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Delivery details
Software as a Service (SaaS)
SaaS delivers cloud-based software applications directly to customers over the internet. You can access these applications through a subscription model. You will pay recurring monthly usage fees through your AWS bill, while AWS handles deployment and infrastructure management, ensuring scalability, reliability, and seamless integration with other AWS services.
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Support
Vendor support
Support requests should be sent to support@deepset.ai . We also provide professional services and solution engineering resources.
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Customer reviews
Clarence Ho
Pipeline framework has transformed how I evaluate RAG models and optimize vector search
Reviewed on May 07, 2026
Review from a verified AWS customer
What is our primary use case?
I have been using Deepset AI Platform for around six months. I use Deepset AI Platform mainly for Gen AI model evaluation for our RAG application. For example, we are using Deepset Haystack open-source platform with a Gen AI evaluation framework called Ragas. We use Haystack to quickly assemble our RAG application pipeline to take the prompts and then interact with our vector database, which is Pinecone , and then process the query, get the response, and then compare it with the reference results provided by humans. We then use the LLM as a judge to perform evaluation and output the score for developers to see in order to evaluate the chunking strategy of their vector database.
What is most valuable?
The best feature Deepset AI Platform offers is the pipeline feature that is very easy for me to compose the large language model as well as the vector database search and retrieval, allowing me to build the application and the evaluation script within a very short period of time.
The pipeline feature and the ease of composing with large language models and vector search save me a lot of time by not writing the code from scratch. I just build the pipeline because Deepset AI Platform provides the out-of-the-box integration with the tools and stack that I am using, including the OpenAI model as well as the Pinecone API. I do not need to implement the details; I just use the existing tools in Haystack, pulling it together for the pipeline. This allows me to avoid too much detailed coding and saves me a lot of work, enabling me to focus on the evaluation.
Deepset AI Platform positively impacts our organization because we previously did not use any framework for Gen AI applications, and the introduction of this stack provides a framework for our team. It lets our team think about it and shows that it is worth introducing a framework in the future.
What needs improvement?
No improvements are needed for Deepset AI Platform.
For how long have I used the solution?
I have been using Deepset AI Platform for around six months.
What other advice do I have?
I do not have anything else to add about my main use case or how I use Deepset AI Platform in my process. I do not want to add anything else about the features. My advice for others looking into using Deepset AI Platform would be to take a look at the documentation to understand how to build the pipeline, as well as the kind of components that are provided out of the box, including the model provider and the vector database provider. Taking a look at the examples and the documentation will help to gain more insight into how to better use Deepset AI Platform. I would rate this product an eight out of ten.
Which deployment model are you using for this solution?
Public Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Amazon Web Services (AWS)