Business automation built around how you actually work

Workflow automation removes a specific friction point with a targeted build. Quote follow up, missed call recovery, job card automation. Business automation is the wider shift of building AI and intelligent systems into how your business operates. Custom AI tools, workflow agents, staff training, internal knowledge systems, and the cultural shift of running an AI native business. Workflow automation is one piece. Business automation is the operating system around it.

Business automation is quoted case by case. There is no fixed price because the scope varies from a single custom AI tool to a multi quarter rollout with internal knowledge systems, agents, and staff training. The standard first paid step is the $495 Workflow Review, which produces a written report mapping where AI and automation add real value to your operation. From there we quote the build work specifically. Most clients see a clear return on the review alone.

We build custom AI tools when off the shelf does not fit, and configure existing platforms when they do. Custom builds include diagnostic tools for technical work, reference systems that hold institutional knowledge, invoicing and quoting applications, customer communication tools, and workflow agents that handle repetitive admin. We integrate Anthropic Claude, OpenAI, and Google Gemini under the hood depending on the use case. Off the shelf is fine when it earns its place. It rarely does at the level of detail an SMB actually needs.

Two things. First, the tool gets designed around how your team already works rather than forcing them into a new pattern. We sit in the operation, watch the real workflow, and build the tool to fit. Second, training is part of the engagement, not an afterthought. Your team gets walked through every tool, gets documentation they can refer back to, and gets a support window after handover. Tools that nobody uses are a waste of money. We treat adoption as part of the build.

For most current builds, data sits with the underlying providers we integrate. Anthropic, OpenAI, and Google all publish their data handling terms and we design integrations around what those terms allow. We avoid model training on your data wherever the provider supports it. Our long term goal is sovereign Australian AI compute. Custom small language models on NVIDIA hardware sitting inside Australian jurisdiction so your customer and business data stays where it should. Builds today are designed with that migration path in mind.

Discovery to first usable tool is usually three to six weeks for a focused build. A wider rollout with multiple custom AI tools, internal knowledge systems, agents, and staff training runs across two to six months in phases. We work in milestones so you see something live and useful every fortnight. Discovery and the Workflow Review sit ahead of the build window and add another one to two weeks depending on scheduling and how clear the brief already is.

Augment. Every PrizmaCore build is designed to take the repetitive admin off your team so they can do the work that actually requires them. Quote chasing, data entry, copy paste between systems, status updates, knowledge lookups. That is what gets automated. The judgment work, the customer relationships, the trade skill, the operational decisions, those stay with your team and get better support from the tools around them. We have never built a system to make a small team smaller. We build them so a small team can run like a bigger one without burning out.