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Services

Four services, one rule: every project starts with a specific process and a metric, not with a technology. If you’re not sure where to start, start with what hurts most and we’ll place it on the first call.

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AI implementation

Who it’s for
Companies that want AI to do real work on their data and systems, not a generic chatbot.
What’s included
LLM assistants and agents, process automation, AI over your documents and databases, integrations with ERP, CRM, email and messaging.
What you get
A pilot with a metric, a production application with a hard spending cap, ongoing evaluation and documentation.
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Custom software

Who it’s for
Companies with a process no off-the-shelf tool covers well.
What’s included
Web applications, customer and vendor portals, internal tools, APIs and integrations.
What you get
Code in your repository, automated tests, AWS deployment, documentation and handover.
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AWS cloud & DevOps

Who it’s for
Teams that want to get rid of servers to patch, clean up deployments, or bring the AWS bill down.
What’s included
Serverless architecture, migration, infrastructure as code, CI/CD with real gates, cost control, security baseline.
What you get
Reproducible infrastructure, a pipeline with gates, a cost report with actions.
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SRE & observability

Who it’s for
Companies with systems in production that don’t know how they’re doing until something breaks.
What’s included
Monitoring, complete alarm views, service-level objectives, incident response, postmortems.
What you get
A plain-language quality dashboard (ozeida Quality Control), reviewed alarms, a response playbook.

How they fit together

Most AI projects need some of the other three: an integration (software), a place to run with controlled cost (AWS), and someone watching that it keeps working (SRE). We quote them together when needed and never sell you what you don’t need.

Not sure which one you need?

Tell us the process you want to improve and we’ll tell you where to start.

Tell us about your project