Avizing Technologies, United States
Apache Hop consultingand AI-native data pipelines
Managing data is hard. We're here to help.
Avizing designs, containerizes, and operates Apache Hop data pipelines that run reliably in your cloud: versioned in Git, secured with a proper secrets manager, backed up, and monitored. AI and large language models are primary contributors to every engagement, in how we build and in what your pipelines can do.
- Apache Hop
- Hop Web
- LLM pipelines
- Docker
- Kubernetes
- Git and CI/CD
- AWS
- Azure
- Google Cloud
Services
Reliable data, end to end
From first assessment to a production platform your team can run, we cover the whole path.
Cloud Adoption & Migration
Move data workloads to AWS, Azure, or Google Cloud with a plan that keeps data reachable, costs predictable, and cutover boring.
Data Handling & Automation
Replace manual hand-offs and one-off scripts with scheduled, monitored Apache Hop workflows so data lands where it should, on time.
Continuous Integration
Bring the same test, build, and deploy discipline to pipelines that your application code already has: every change reviewed, versioned, and promoted through environments.
ETL / ELT
Design extraction, transformation, and loading flows that scale with your sources, survive schema change, and are easy to hand over.
What we do
Three ways in
Most engagements start from one of these. Each has its own page with the detail.
Apache Hop consulting
Adopt Hop and run it properly: projects in Git, Hop Server and Hop Web in containers, and a cloud-native runtime on AWS, Google Cloud, or Azure.
Apache Hop servicesPentaho and Kettle migration
Move transformations and jobs to Hop with an inventory, automated import, remediation, side-by-side verification, and a cutover you can roll back.
How we migrateAI-native data pipelines
Pipelines built with AI coding assistants, and pipelines that call an LLM as a step, with redaction, validated output, and cost controls built in.
AI-native delivery
Enterprise ready by default
The unglamorous parts, done first
A pipeline that works on one laptop is a demo. These four practices are what turn it into a platform.
- 01
Git-based lifecycle
Projects and environment configuration live in Git. Every change is reviewed in a pull request, versioned, and promoted from development to test to production by CI, never edited on a server. AI-assisted changes follow exactly the same path.
- 02
Secure credential management
No passwords in pipelines, images, or repositories. Connections resolve at run time from HashiCorp Vault, AWS Secrets Manager, Azure Key Vault, or Google Secret Manager, using least-privilege identities that can be rotated.
- 03
Backups and recovery
Metadata, configuration, and run history are snapshotted on a schedule to durable object storage, and restores are rehearsed, so recovery is a procedure rather than a hope.
- 04
Monitoring and alerting
Structured logs, metrics, and run status flow into the observability stack you already use, whether Prometheus and Grafana, CloudWatch, Azure Monitor, or Datadog. Failures and stuck runs alert the right people.
How we work
From assessment to hand-over
Fixed scope, clear milestones, and a platform your own team runs at the end.
- 1
Assess
Inventory the pipelines, environments, and pain points you have today, and agree on what done looks like.
- 2
Design
Target architecture, environment strategy, security model, and runbooks, with options explored alongside AI assistants and reviewed with your engineers before anything is built.
- 3
Deploy
Containerize, wire up CI/CD, migrate pipelines in slices, and cut over with rollback ready at every step.
- 4
Operate and hand over
Monitoring, documentation, and training for your team, with optional ongoing support if you want a second pair of eyes.
Our approach
Open source, no lock-in
We build on Apache Hop and other open source tools so our clients own their pipelines outright, avoid vendor-dependent integrations, and keep the flexibility to change direction as the market does.
- Your pipelines are plain files in your own Git repositories.
- Portable containers run the same on any cloud or on-premises.
- No per-seat licenses, no proprietary runtime to renew.
- Hop complements Databricks, Snowflake, BigQuery, and dbt rather than replacing them.
Get in touch
Free Consultation
Tell us about your data platform, or the one you wish you had. A short call is usually enough to say whether we can help and what it would take.
Based in the United States, working with domestic and international clients across time zones.
- Phone(877) 881-6238