Managed Vector Databases
- Index design & tuning
- Hybrid semantic + metadata filtering
- Horizontal scaling
Vector Databases
Pinecone, Weaviate, Milvus & pgvector
Semantic search and retrieval infrastructure sized to your data volume and existing stack.
Why Vector Search Matters
Traditional keyword search misses relevant results that don't share exact keywords, but not every team needs a dedicated vector database either. We size the solution to your data — pgvector when you're already on Postgres, dedicated vector databases when scale genuinely demands it.
The Business Impact
- Better Search Relevance
Semantic retrieval finds conceptually related results, not just keyword matches.
- Right-Sized Infrastructure
pgvector avoids new infrastructure for smaller-scale needs.
- Low Query Latency
Sub-100ms retrieval keeps RAG and search features responsive.
Where We Work
From a single pgvector column to a dedicated vector cluster.
Self-Hosted Options
- Self-hosted cluster setup
- Cost-optimized for high volume
- Backup & disaster recovery
pgvector
- No new infrastructure to operate
- Combined relational + vector queries
- Lower cost at small-to-mid scale
How We Help
From index design to keeping embeddings fresh.
Vector Search Implementation
Semantic search that scalesWe design and tune the retrieval index — managed or self-hosted — for your data volume and latency targets.
<100ms
Target Latency
- Index design & tuning
- Hybrid semantic + metadata filtering
- Latency benchmarking
Embedding Pipeline & Maintenance
Keep the index currentIngestion pipelines that re-embed and re-index changed records automatically as your data changes.
99%
Vector Index Uptime
- Automated re-embedding pipelines
- Incremental re-indexing
- Index health monitoring
What This Looks Like in Practice
Results teams see after adding semantic retrieval.
Higher
Search relevance
Semantic retrieval surfaces conceptually relevant results keyword search misses.
<100ms
Query latency
Target retrieval latency for production RAG and search features.
Right-sized
Infrastructure cost
pgvector avoids new infrastructure entirely for smaller-scale needs.
Why Teams Choose Us
We size vector infrastructure to your data, not to what's trending.
Sized to Your Scale
We won't sell you a dedicated vector cluster if pgvector already covers your needs.
- pgvector recommended where it fits
- Dedicated clusters only at real scale
Kept Fresh Automatically
Ingestion pipelines re-embed and re-index changed data without manual intervention.
- Automated re-embedding pipelines
- Zero manual re-indexing required
Latency-Tested
Every index is benchmarked against real latency targets before it ships.
- Sub-100ms latency benchmarking
- 99% index uptime target
Frequently Asked Questions
Common questions about our Vector Databases and implementation services.