Qdrant Cloud Inference lets you generate embeddings for text, image, and sparse data directly inside your managed Qdrant cluster. Better latency, lower egress costs, simpler architecture, and no external APIs required.
The community submitted 23 reviews to tell
us what they like about Qdrant Cloud Inference, what Qdrant Cloud Inference can do better, and
more.
5.0
Based on 23 reviews
Review Qdrant Cloud Inference?
Reviewers describe Qdrant Cloud Inference in narrow but consistent terms: fast, easy to set up, well documented, and flexible enough to support many query types. One user says it now powers their RAG, vector search, agent context, and other data-heavy workloads, suggesting it holds up in production use. The only clear criticism is that vector visualization needs work. Founder reviews are uniformly positive, but they contain no usable detail, so the strongest evidence comes from this single hands-on user account.
+20
Summarized with AI
Pros
Cons
Tines The single, secure environment for agents, apps, and automations.
It is fast, has a great docs, supportaall types of queries that one can need. The setup is simple. And it now powers our RAG, vector search and our agent context and much more for our data intensive workloads.
What needs improvement
I cannot find Qdrant in the products for a shoutout. Idk why. But since I love your product .. I had to leave a review.
The only thing that needs some love is the vector visualization. Happy to help here ;)
We use Qdrant to store and search high-dimensional vector embeddings of malicious patterns, phishing URLs, and threat indicators. This empowers Truelink to compare new threats against known vectors instantly using semantic AI.
After evaluating a bunch of Vector DBs to be our internal vector DB, we finally closed on QDrant because it was the one that scaled the best and had the best price performance ratio
We evaluated a bunch of vector DBs—and Qdrant stood out for its blazing speed, filtering, and hybrid search. It's the unsung hero that lets our AI agents recall and reason across docs, CRMs, and conversations in milliseconds.