Vector Pulse

Intelligent data. Practical AI. Custom software.

A technology company that builds data platforms, AI systems and custom software for clearer operations and better decisions.

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What we do

Technology for companies that grow on data

End-to-end delivery across data infrastructure, artificial intelligence and bespoke software. Built for reliability and real operational impact.

01

Data Engineering

Pipelines, warehouses and lakehouse architectures that turn fragmented sources into a trusted foundation for analytics and AI.

  • ETL / ELT & streaming pipelines
  • Data warehouses & lakehouses
  • Quality, lineage & observability
  • Python
  • SQL
  • Apache Spark
  • Airflow
  • dbt
  • Kafka
02

Artificial Intelligence

Practical AI systems that automate work, surface insight and support decisions, integrated into the tools your teams already use.

  • ML models & predictive analytics
  • LLM / RAG applications
  • Intelligent process automation
  • PyTorch
  • scikit-learn
  • LangChain
  • OpenAI / Azure OpenAI
  • pgvector
03

Custom Software

Purpose-built platforms and applications designed around your workflows: scalable, maintainable and ready for production.

  • Business platforms & portals
  • API & system integrations
  • Cloud-native applications
  • TypeScript
  • Python
  • React
  • FastAPI
  • Docker
  • PostgreSQL

Vector Pulse Kft.

Vector Pulse Kft. is a technology company specializing in data engineering, artificial intelligence and custom software development. We design intelligent data platforms, automation solutions and AI-powered applications that help businesses optimize operations and make data-driven decisions.

Based in Budapest, we partner with organisations that need reliable engineering, not slide decks. From data infrastructure to production AI and bespoke software, we build systems that stay useful after launch.

Outcomes we deliver

From raw data to intelligent products: systems that optimize operations and make data-driven decisions possible.

Platform Data engineering

Intelligent data platforms

Unified platforms that collect, transform and serve data across the organisation, ready for BI, AI and operational use.

  • Spark
  • Airflow
  • dbt
  • Snowflake
  • BigQuery
Automation Operations

Automation solutions

Workflow automation that removes repetitive work, reduces errors and frees teams to focus on higher-value decisions.

  • Temporal
  • Kafka
  • REST / GraphQL
  • Docker
  • Kubernetes
AI Applied intelligence

AI-powered applications

Custom applications that embed AI into products and internal tools: assistants, ranking, classification and generation.

  • LangChain
  • RAG
  • PyTorch
  • OpenAI API
  • Hugging Face
Insight Decision support

Data-driven decisions

Clear metrics, reliable reporting and decision support so leadership can act on evidence, not intuition alone.

  • Power BI
  • Looker
  • Metabase
  • SQL
  • dbt metrics

Process

A delivery system built for data & AI

Engineering precision from discovery to production. Each stage turns your goals into a working system your business can rely on.

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  1. 01

    Discovery & scoping

    We map data sources, business goals and constraints, then define a clear technical scope for platforms, AI use cases or custom software.

  2. 02

    Architecture & design

    Solution architecture for data flows, model strategy and application structure, designed for scale, security and maintainability.

  3. 03

    Data foundation

    Pipelines, storage and quality controls that establish a trusted data layer: the backbone for analytics and AI.

  4. 04

    Build & integrate

    We develop platforms, models and applications, integrate with your stack, and iterate with working increments you can evaluate early.

  5. 05

    Validation & hardening

    Testing, performance tuning and operational checks so the system holds up under real load and real users.

  6. 06

    Launch & evolve

    Production deployment, monitoring and a clear path for the next iteration, so value compounds after go-live.

Questions about working with Vector Pulse

Practical answers on engagement, delivery and what we need to start a data, AI or software project.

What kinds of projects do you take on?

We focus on data engineering, artificial intelligence and custom software: from data platforms and pipelines to AI-powered applications and business systems that need to run in production.

How does a typical engagement start?

We begin with a short discovery call to clarify goals, data sources, constraints and success criteria. From there we propose a scoped plan (architecture, timeline and next milestones) before any large build commitment.

Do you work with existing systems and cloud stacks?

Yes. Most projects integrate with tools and infrastructure you already use: databases, warehouses, APIs, CRM/ERP and cloud environments. We design for fit, not for unnecessary rewrites.

What do you need from us before kickoff?

A clear business goal, access to relevant stakeholders, and an overview of current data sources or systems. Detailed documentation helps, but we can also map the landscape together during discovery.

How long does a project usually take?

It depends on scope. Focused integrations or MVPs can move in weeks; full data platforms or multi-system AI products often run across several months with staged deliveries so you see working increments early.

Can you support us after launch?

Yes. We can hand over a maintainable system, stay on for monitoring and iteration, or help your internal team take ownership, whichever fits your operating model.

Tell us about your project

Share a short brief: data platform, AI initiative or custom software. We will get back to you to discuss next steps.