RAG & AI Systems
Your data, answering questions accurately, on infrastructure you control. Private by design: on your hardware, in your tenant, or fully offline — with source citations on every answer.
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// a Triton Technologies company
Custom software, RAG and AI systems, workflow automation, modernization, and the security and compliance checks that make it defensible. Engineered for clients worldwide by the development division of a company that has kept businesses running since 2001.

01 / services
Your data, answering questions accurately, on infrastructure you control. Private by design: on your hardware, in your tenant, or fully offline — with source citations on every answer.
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Software shaped to your operation, not the other way around.
Explore →AI wired into the tools you already run, with guardrails.
Explore →Kill the swivel-chair work between your systems.
Explore →Web apps that load fast, stay up, and age well.
Explore →Find the hours your workflows are leaking, then take them back.
Explore →Your twenty-year-old system doesn't need a funeral. It needs an engineer.
Explore →AI systems create new attack surface. We check it before someone else does.
Explore →Use AI aggressively. Defend it on paper.
Explore →Discovery, written specification, milestone builds, verification, support. No surprises, by design.
How we work →02 / why a foundry
Foundry is a division of a managed IT provider, not a standalone studio. Everything ships with monitoring, backups, documentation, and a support path — because we are usually the ones supporting it at 2 a.m.
RAG and AI systems that can run entirely on your hardware, in your cloud tenant, or fully offline. Your documents and prompts stay under your control, with citations on every answer and governance on paper.
Fixed quotes against written specifications. Milestone billing you can see. IP and licensing terms defined before code starts. The absence of surprises is a deliverable.
03 / insights
Jul 15, 2026
When buying SaaS beats building custom software and when it quietly stops making sense: a practical framework covering fit, per-seat math, integration debt, and exit risk.
Jul 15, 2026
An engineering comparison of off-the-shelf RAG platforms and custom retrieval builds: cost structure, data control, accuracy on messy data, and when each wins.
Jul 15, 2026
A plain-language explanation of development retainers: what the monthly block covers, how prioritization works, and how to judge whether a retainer is healthy.
// next step
Tell us what you are trying to build or fix. A senior engineer reviews every inquiry and responds with a straight answer, not a sales script.