Schema & module design
Modelling classes, properties and the right vectorizer modules so retrieval matches your domain is easy to get wrong and costly to refactor later.
Weaviate Vector DB Hybrid Search Multi-Tenancy
Weaviate vector database development
We design, build and operate Weaviate deployments for US and EU companies that need production-grade semantic and hybrid search. From schema and module design to multi-tenant RAG backends, we deliver Weaviate on your own infrastructure or on Weaviate Cloud. Our engineers tune retrieval quality, isolate tenants and keep data resident in the right jurisdiction for GDPR and HIPAA.
We design, build and operate Weaviate deployments for US and EU companies that need production-grade semantic and hybrid search. From schema and module design to multi-tenant RAG backends, we deliver Weaviate on your own infrastructure or on Weaviate Cloud. Our engineers tune retrieval quality, isolate tenants and keep data resident in the right jurisdiction for GDPR and HIPAA.
Challenges
Industry challenges we solve
Hybrid search tuning
Balancing BM25 keyword scoring with vector similarity, and tuning the alpha weighting, is critical for relevance but rarely tuned correctly out of the box.
Multi-tenancy at scale
Thousands of isolated tenants demand careful sharding, activation strategy and per-tenant lifecycle management to avoid noisy-neighbour and memory blow-ups.
Memory & resource management
HNSW indexes are memory-hungry; without the right vector cache, quantisation and node sizing, costs and latency spiral as data grows.
Self-host ops vs Weaviate Cloud
Choosing between running Weaviate on Docker/Kubernetes and using Weaviate Cloud affects cost, control, residency and operational burden.
Vectorizer choice & embedding sync
Selecting embedding models and keeping vectors in sync as source data and models change is a frequent source of stale or mismatched search results.
Solutions
Solutions we build
Weaviate schema & module setup
We design your collection schema, configure vectorizer and reranker modules, and validate retrieval against real queries before go-live.
Hybrid search tuning
We combine BM25 and vector search, tune the alpha weighting and add reranking so results stay precise across keyword and semantic intents.
Multi-tenant architecture
We implement Weaviate native multi-tenancy with tenant activation, isolation and lifecycle controls that scale to large tenant counts cleanly.
Resource & scaling optimisation
We size nodes, configure HNSW parameters, vector quantisation and caching, and benchmark latency and recall to control cost at scale.
Self-host or Cloud deployment
We deploy Weaviate on Docker or Kubernetes in your VPC, or on Weaviate Cloud, with backups, monitoring and zero-downtime upgrades.
RAG backend integration
We wire Weaviate into your RAG and application backends, manage embedding pipelines and keep vectors in sync with your source systems.
Stack
Technology stack
Weaviate, vectorizer modules, hybrid search (BM25 + vector), multi-tenancy, GraphQL/REST, Weaviate Cloud, self-host (Docker/K8s), embeddings.
Compliance
Compliance & regulations
GDPR · self-host data residency · HIPAA-ready · SOC 2
EU
- GDPR — self-host Weaviate inside the EU with per-tenant data erasure and multi-tenancy isolation, so personal data and embeddings never leave your control.
- EU AI Act — transparent, auditable retrieval pipelines and documented vectorizer choices that support obligations for high-risk and general-purpose AI systems.
- Data residency & sovereignty — pin Weaviate clusters and embedding generation to EU regions or on-premise to meet sovereignty and contractual requirements.
- NIS2 — hardened cluster operations, access controls and monitoring aligned with NIS2 expectations for essential and important entities.
US
- HIPAA — deploy Weaviate self-hosted in your own VPC with encryption and access controls so PHI and its embeddings stay within your boundary.
- NIST AI RMF — retrieval and embedding pipelines mapped to the govern, map, measure and manage functions for trustworthy AI.
- SOC 2 — audit logging, least-privilege access and change controls that fit into your SOC 2 security and availability programmes.
- CCPA/CPRA — per-tenant deletion and data inventory support consumer access and erasure requests across stored objects and vectors.
Cases
Selected Weaviate case studies
Retail · Document Management
Document Management System
An internal EDM for a retail chain — e-signatures, approval routing, counterparties, and tasks on React + Laravel, built for US & EU operations.
HealthTech · Diagnostics
Unilab
Patient app for a 40-city lab network — appointment booking, digital results, 2,500+ tests, scheduling and accounting integrations.
Sports Media · Mobile
Media Arena
Cross-platform sports news app and web portal — Telegram-bot CMS instead of a custom admin, Markdown publishing pipeline.
Why YuSMP
Why teams choose YuSMP for Weaviate development
Compliance-first deployments
We default to self-hosting in your region or VPC, so GDPR, HIPAA and data-residency requirements are met by design, not bolted on.
Retrieval quality you can measure
We benchmark recall, precision and latency, and tune hybrid search and HNSW so your search and RAG actually improve, not just ship.
Senior engineers, end to end
One team owns schema, modules, multi-tenancy, scaling and integration — no hand-offs between strategy and the people writing the code.
FAQ
Weaviate Development FAQ
How does Weaviate compare to pgvector, Qdrant or Pinecone?
pgvector is great when you already run PostgreSQL and have modest vector volumes. Qdrant and Pinecone are dedicated vector databases like Weaviate. Weaviate stands out with built-in vectorizer modules, first-class hybrid search and native multi-tenancy, plus a choice of self-host or Weaviate Cloud. We help you pick based on data residency, scale and operational preferences rather than hype.
What is the advantage of Weaviate hybrid search?
Hybrid search blends BM25 keyword scoring with vector similarity in a single query, so you catch both exact-term matches and semantic meaning. By tuning the alpha weighting and adding reranking, we deliver relevance that pure keyword or pure vector search cannot match, especially for product, document and knowledge-base search.
What are Weaviate built-in vectorizer modules?
Weaviate can generate embeddings for you through pluggable modules for providers and self-hosted models, so vectors are created at import and query time without a separate pipeline. We configure the right module for your domain, or wire in your own embeddings when you need full control over the model.
Does Weaviate support multi-tenancy?
Yes. Weaviate has native multi-tenancy that isolates each tenant's data within a collection, with per-tenant activation and deletion. We design the tenant model, manage activation strategy and ensure isolation and per-tenant erasure scale to large customer counts.
Should we self-host Weaviate or use Weaviate Cloud?
Self-hosting on Docker or Kubernetes gives full control over data residency, cost and tuning, and is our default for HIPAA and strict GDPR cases. Weaviate Cloud reduces operational burden and is a strong fit when residency allows. We assess both against your compliance, scale and team capacity, and can migrate either way.
How does Weaviate scale as our data grows?
Weaviate scales horizontally with sharding and replication, while HNSW tuning, vector quantisation and caching keep memory and latency in check. We benchmark recall and latency at your target volume, size nodes accordingly and plan a scaling path so performance holds as data and tenants grow.
How does self-hosting Weaviate help with GDPR?
Self-hosting Weaviate inside the EU keeps all objects and embeddings within your chosen jurisdiction, so personal data never leaves your control. Combined with multi-tenancy isolation and per-tenant deletion, this supports data residency, the right to erasure and your wider GDPR obligations.
Build your Weaviate vector search with confidence
Response within 1 business day. NDA on request.