Enterprise Qdrant Engineering
The high-performance vector similarity search engine, written in Rust for speed and reliability. We design, optimize, and deploy production-grade architectures utilizing the full capabilities of the Qdrant ecosystem.
Qdrant
Production Certified
Qdrant is our database of choice for projects requiring high-performance vector search, memory safety, and rich payload filtering. Written in Rust, Qdrant provides fast queries and stable scaling on standard servers.
Our Qdrant Engineering Services
We deliver highly specialized, production-ready systems tailored to your technical requirements.
Qdrant Collection Setup
We set up Qdrant collections, configuring vector distance metrics and payload schemas.
Payload Filtering Optimizations
We write complex payload queries in Qdrant, filtering results by categories, tags, or dates before similarity checks.
Distributed Clustering
We deploy Qdrant clusters on Kubernetes, configuring sharding, replication factors, and load balance routes.
In-Memory Vector Search
We optimize Qdrant configurations, balancing in-memory storage and disk payloads to reduce server memory overhead.
Qdrant Tooling & Stack Integrations
We operate across the entire modern ecosystem surrounding Qdrant, deploying optimized dependencies and configurations.
Qdrant Clients
Core SDK libraries used to communicate with Qdrant.
Underlying Tech
Technologies driving Qdrant's performance.
Monitoring
Tools used to track database health.
Production-Grade Engineers
Top 1% Seniority
Experienced database architects deploying memory-efficient Qdrant clusters.
Immediate Velocity
Optimized query latencies utilizing payload filtering and segment indexes.
Compliance Native
Secure hosting, configuring Qdrant inside private cloud environments.
Proven Results with Qdrant
Explore how we leverage Qdrant to build business-critical platforms and achieve operational milestones.
Qdrant Vector Search Index Scales to Support 2 Million Profiles
We built a search engine in Qdrant, using payload filters to restrict matches to active subscriptions, keeping query latency under 10ms.
Telemetry Similarity Engine Matches Routing Logs
Designed a telemetry indexing pipeline in Qdrant, matching daily truck paths with historic route records.
Flexible Engagement Models
Scale your engineering capacity dynamically. We integrate seamlessly into your operations with three battle-tested engagement models.
Staff Augmentation
Inject senior AI and MLOps engineers directly into your active squads. Rapidly scale resources with dedicated support under your management.
Dedicated Team
A self-governing team of engineers, project managers, and QA specialists built specifically to design, build, and support your proprietary AI pipelines.
Full Build & Deliver
Fixed-scope or milestone-driven development. We take ownership from requirements definition and MVP design to final production handoff.
Compliance-First Deployment Standards
We integrate safety controls natively. Every Qdrant application is architected to satisfy strict global compliance and privacy policies.
SOC 2 Type II
Logical isolation & logs
HIPAA PHI
PHI data de-identification
ISO/IEC 27001
International safeguards
Common Qdrant Questions
Why do you use Qdrant over other vector databases? expand_more
How do you connect to Qdrant? expand_more
What is Payload Filtering in Qdrant? expand_more
Does Qdrant support sharding? expand_more
How do you optimize Qdrant memory footprints? expand_more
Accelerate Your AI Project with Qdrant
Schedule an architectural blueprint review session with our senior Qdrant engineers to map your database, compliance, and MLOps strategies.