Kern Vector helps organisations build and operate production systems where software, data, and AI meet. We favour clear outcomes over open-ended process: ship the change, leave ownership boundaries intact, and keep failure modes teams can reason about.
Data Platforms & Engineering
We design and improve data platforms that move signals from operational systems into decision-ready pipelines.
Typical work includes:
- Batch and streaming ingest, transformation, and serving paths
- Cloud data platforms on AWS and Azure
- Pipeline tooling such as Spark, Airflow, Kafka, dbt, and SQL warehouses
- Making platforms operable: ownership boundaries, observability, and maintainable delivery
Software Systems
We build and simplify backends and APIs that must behave under load — and reduce systems that have become too fragile or overengineered to change safely.
Typical work includes:
- Go and Python services with clear interfaces
- High-throughput pipelines and performance-sensitive paths
- Breaking complex systems into components teams can own
- Delivery practices that favour repeatable releases over heroics
Machine Learning & Applied AI
We help teams take machine learning and GenAI from experiment to production: packaging, serving, monitoring, and the operational choices that determine whether a system can be trusted.
Typical work includes:
- Operational machine learning and computer vision pipelines
- Model serving with routing, fallback, and observability
- GenAI grounded in company data, with clear tool and agent boundaries
- Architecture reviews for AI readiness and serving strategy
Automation & Integration
We connect systems and automate workflows so teams spend less time on glue and manual process.
Typical work includes:
- Workflow automation for recurring operational tasks
- Integrations between internal tools, data stores, and external APIs
- Lightweight services where a workflow tool is not enough
- Practical automation that is documented and operable by the team that inherits it
Engagement
Projects
Best when there is a defined outcome: a platform to rescue, a pipeline to ship, or an AI system to put into production.
- Intro conversation — fit, constraints, and urgency
- Optional short discovery
- Written scope — outcomes, assumptions, and timeline
- Delivery with observability and handover
- Optional follow-on advisory
Advisory
Time-boxed architecture and platform reviews. Useful when a team needs a clear plan before a larger build: data platform structure, AI serving strategy, or how to simplify a system that has become hard to operate.
Contracting / Detachering
Best when a team needs senior capacity embedded in the backlog — data engineering, backend systems, or production AI — measured by shipped outcomes, not ticket volume alone.
We work in English with technical stakeholders and leave systems easier for the team to run after the engagement ends.
What We Do Not Offer
Kern Vector is not a managed GPU host, a clinical genomics practice, a chatbot-in-a-week shop, or a full-service digital agency. If the problem is production software, data, or AI that must stay operable, we are likely a fit.