01
Build
New products and platforms, designed to be changed later.
We engineer AI into the systems your business runs on.
From LLM features and data platforms to cloud infrastructure and CRM, we design, build, and operate technology that holds up in production — and that your own team can run after launch.
Who we are
We engineer systems that survive the real world — and leave them in a state your own team can run.
Nodeblix is an AI-first technology engineering and consulting company. We design, build, modernize, and help operate AI applications, cloud platforms, delivery pipelines, custom software, data platforms, analytics, and CRM systems.
Most technology programmes stall for unmysterious reasons: unclear ownership, fashionable architecture, data nobody trusts, and a handover that never quite happens. AI raises the stakes on all four. We are organised around those failure modes.
About NodeblixWhat we do
Build. Modernize. Operate.
Three kinds of work, one standard: systems that can be explained, changed, and run after we leave the room.
02
Modernize
Move the estate forward without stopping the business that runs on it.
03
Operate
Release, observe, and decide with evidence — after launch, on purpose.
Services
Eight capabilities, one operating estate.
Each service has its own failure modes. The useful work is knowing which one is actually blocking the business — and what has to move with it.
AI Engineering
LLM applications, retrieval over your own knowledge, AI agents, and the evaluation and MLOps that keep them dependable after launch.
- LLM application development
- Retrieval-augmented generation (RAG)
- AI agents and workflow automation
- Evaluation and guardrails
Industries
Industry context, not sector slogans.
Regulated change, seasonal peaks, plant-floor reality, sensitive records. We plan around the constraints each sector actually carries.
How we work
Five movements. No black box.
Short discovery, written trade-offs, and delivery that lets the organisation keep operating while the system changes underneath it.
- 01Discover
Goals, systems, constraints, and who will live with the result.
- 02Define
Architecture, milestones, and what “good” looks like — written down.
- 03Engineer
Design, build, integrate, and test in realistic conditions.
- 04Launch
Deploy with monitoring and a rollback that has been rehearsed.
- 05Evolve
Reliability, cost, and usability after the first release.
Work
How we think, shown as method.
Illustrative scenarios — not named clients or invented results. Authorised case studies will be published with approved outcomes.
All scenarios
Insights
Notes from the work.
Practical writing on AI, migration, delivery, architecture, and data — for people who have to live with the system.
AI EngineeringTaking an LLM feature from demo to production: what changes after the prototypeRead article →
Cloud & InfrastructureCloud migration planning: the risks that appear after the kickoffRead article →
DevOps & ReliabilityCI/CD pipeline design that a team will still understand in a yearRead article →Software ArchitectureMonolith versus microservices is the wrong first questionRead article →
Data EngineeringData pipeline reliability is a production problemRead article →Data EngineeringWarehouse or lakehouse: choose the constraint, not the labelRead article →
Analytics & Decision IntelligenceDesigning business intelligence people will keep openRead article →
CRM & Enterprise SystemsCRM integration and data migration without a second source of truthRead article →Software ArchitectureModernizing a legacy application without a heroic rewriteRead article →Cloud & InfrastructureCloud cost governance without a theatre of dashboardsRead article →DevOps & ReliabilityObservability and production readiness are the same projectRead article →FAQ
Questions about working with Nodeblix
What does Nodeblix do?
Nodeblix is an AI-first technology engineering and consulting company. We design, build, modernize, and help operate AI applications — LLM features, retrieval over company knowledge, and AI agents — together with the cloud infrastructure, CI/CD and DevOps practices, custom software, microservices architectures, data platforms, analytics, and CRM systems they depend on.
What does “AI-first” mean in practice?
It means we consider where AI can genuinely improve a workflow at the start of every engagement, and engineer it with the same discipline as any other production system: grounded in reliable data, tested against real cases, monitored, and owned. It does not mean adding a model where a simpler rule or report would do the job.
Who are Nodeblix services for?
Technology and business leaders — CTOs, CIOs, engineering managers, and data leaders — in organisations whose operations depend on their systems. Our industry pages cover the constraints we plan around in financial services, retail, manufacturing, healthcare, logistics, and software companies.
Which technologies and platforms do you work with?
We design for the major cloud providers — AWS, Microsoft Azure, and Google Cloud — and implement common CRM platforms such as Salesforce, HubSpot, and Microsoft Dynamics 365. For AI features, we choose per use case between commercial model APIs, the managed model services on those clouds, and open-weight models you can host yourself. For languages, data tools, and BI platforms, we start from what your team already runs and can hire for, rather than introducing a stack for its own sake.
How do the eight services fit together?
AI engineering builds models into products and workflows, and depends on everything beneath it. Cloud engineering provides the platform, and DevOps engineering is how change reaches it. Software development and microservices architecture shape the applications. Data engineering makes information reliable, analytical platforms turn it into decisions, and CRM solutions connect it to customers. Most engagements start with one service and touch two or three.
How does an engagement start?
Describe the systems involved, the constraint that matters, and a rough timeline through the enquiry form. We reply with a suggested first step: a conversation, a scoped assessment, or a clear note that we are not the right fit.
Start a conversation
Have a system that needs to last?
Tell us what you are working on, where the current systems fall short, and what must not break. An engineer reads every enquiry.
- Describe the workSystems involved, constraints, and a rough timeline.
- We read it properlyFit is judged on the problem, not on the size of the budget.
- A useful first stepA short conversation, a suggested scope — or a clear “not us”.