Neural Vector Systems

Technology Stack

Every tool is selected for production reliability, enterprise interoperability, and documented performance at scale. No experimental frameworks in client infrastructure.

Data Platforms

Snowflake

Cloud data warehouse for secure analytics and governed reporting at enterprise scale.

Google BigQuery

Managed analytics platform for large operational datasets and fast decision support.

PostgreSQL

Reliable relational database for core business applications and transactional workloads.

Apache Airflow

Workflow orchestration for scheduled data movement, quality checks, and reporting pipelines.

Apache Kafka

Event streaming backbone for high-volume operational telemetry and real-time integrations.

ML Operations

AWS SageMaker

Managed model training and deployment with production monitoring and versioned releases.

Vertex AI

Google Cloud managed platform for model lifecycle, deployment, and governed experimentation.

MLflow

Model tracking and release management for repeatable experiments and controlled promotion to production.

Grafana

Operational dashboards and alerts for service health, model performance, and deployment stability.

Cloud & Infrastructure

AWS

Scalable cloud environment for compute, storage, secure networking, and production operations.

Google Cloud Platform

Cloud platform for containerized services, managed data systems, and enterprise integrations.

Docker

Container packaging for consistent deployment behavior across development, staging, and production.

Kubernetes

Container orchestration for resilient scaling, high availability, and rolling updates.

GitHub Actions CI/CD

Automated build, test, and release pipelines on every approved change.

Terraform

Infrastructure as code for repeatable cloud setup, governance, and disaster recovery planning.

Technology Selection Principles

01

Production-Proven Over Bleeding-Edge

Every tool in this stack has proven production reliability at enterprise scale. We do not introduce experimental frameworks into client infrastructure.

02

Interoperability Over Ecosystems

Tools are selected for their ability to integrate with existing enterprise infrastructure—not to create new vendor dependencies.

03

Open Standards Where Possible

Portable containers, standard APIs, and infrastructure as code keep deployments flexible and reduce vendor lock-in.

04

Cost-Aware Architecture

Cloud infrastructure is designed with cost optimization embedded from the start—not retrofitted after bills arrive.

Have a Specific Stack Requirement?

Existing cloud agreements, compliance mandates, or preferred tooling? We integrate with what you have.

Discuss Technical Requirements