Enterprise Pinecone Engineering
The cloud-native vector database, built for fast, serverless vector search and production RAG. We design, optimize, and deploy production-grade architectures utilizing the full capabilities of the Pinecone ecosystem.
Pinecone
Production Certified
Pinecone is our vector database of choice for serverless, low-latency semantic search applications. We design Pinecone indexes with optimal distance metrics, manage namespace partitions, and scale vector search to support millions of profiles.
Our Pinecone Engineering Services
We deliver highly specialized, production-ready systems tailored to your technical requirements.
Vector Index Architecture
We configure Pinecone indexes (cosine/dot-product distance), sizing vector dimensions to match embedding models.
Namespace & Metadata Filtering
We organize vector spaces using namespaces, writing metadata filters to restrict search permissions.
Serverless Scaling & Tuning
We deploy and scale Pinecone Serverless configurations, monitoring search latencies and optimizing index writes.
Hybrid Search Integration
We build hybrid search engines, combining Pinecone vector metrics with sparse BM25 text queries.
Pinecone Tooling & Stack Integrations
We operate across the entire modern ecosystem surrounding Pinecone, deploying optimized dependencies and configurations.
Pinecone API
Core Pinecone SDK libraries and clients.
Embedding Bridges
Embedding models generating vectors for Pinecone.
Observability
Monitoring stacks capturing query times.
Production-Grade Engineers
Top 1% Seniority
Expert database administrators specializing in vector dimensioning and distance calculations.
Immediate Velocity
Optimized query performance utilizing namespace filters and hybrid search.
Compliance Native
Enterprise security, configuring Pinecone inside private cloud VPC VPCs.
Proven Results with Pinecone
Explore how we leverage Pinecone to build business-critical platforms and achieve operational milestones.
Pinecone Search Index Scales to Support 5 Million Articles
We constructed a Pinecone Serverless index for a knowledge base app, keeping semantic query response times under 15ms.
Metadata Filtering Engine Secures Client Account Data
Implemented a Pinecone namespace architecture, ensuring financial agents can only query data matching their accounts.
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 Pinecone 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 Pinecone Questions
What distance metrics do you recommend in Pinecone? expand_more
What is Pinecone Serverless? expand_more
How do you handle database updates (Upserts)? expand_more
Can Pinecone run inside our private VPC? expand_more
How do you combine sparse and dense search? expand_more
Accelerate Your AI Project with Pinecone
Schedule an architectural blueprint review session with our senior Pinecone engineers to map your database, compliance, and MLOps strategies.