AU owned Perth WA. Websites, WordPress support, apps and integrations. Very affordable small-business pricing. Free fit check before scope. Fixed-price options for clear work. Australia-wide support. No outsourcing or offshore handoff. Phone +61 3 6413 4207. Phone and email support.
AI integration for small and medium business 4-8 weeks

AI integration for business systems, apps and portals

AI model integrations inside websites, CRMs, portals, dashboards and internal tools. We work across major model providers including GPT and OpenAI, Anthropic Claude, Google Gemini, Microsoft Azure AI, Meta Llama, Mistral, Cohere, DeepSeek, xAI Grok and Amazon Bedrock-hosted models, with prompts, retrieval, guardrails, logging and human review handled properly.

Quick answer on AI integration

Small and medium businesses that want AI inside a real workflow, with the model chosen around the job rather than a single vendor assumption.

AI integration connects a suitable model to your website, CRM, portal or internal tool through a controlled API workflow. The build can use major model families and providers such as GPT and OpenAI, Anthropic Claude, Google Gemini, Microsoft Azure AI, Meta Llama, Mistral, Cohere, DeepSeek, xAI Grok or Amazon Bedrock-hosted models, with prompts, retrieval, permissions, logs, cost controls, evaluations and human review planned around the job.

AI integration connects a model to an existing workflow. If the task is still unclear, start with AI consulting. If the surrounding software does not exist yet, the scope may also need application development. Our Good Designs work summary covers a CRM and AI engagement.

When this is not a fit

Connecting a model without checking data handling, permissions and usage costs is not a production integration. Some information or actions should remain outside the model workflow.

Ask about AI Integration

When AI integration makes sense

Small and medium businesses that want AI inside a real workflow, with the model chosen around the job rather than a single vendor assumption.

Staff are copying work into public AI tools without a safe workflow

A promising AI prototype is not connected to the real system

Documents need source-aware AI answers

The business needs model choice, data handling and review rules explained clearly

What AI integration includes

Your AI Integration scope defines the work below, what your team needs to supply and how the result will be accepted. We confirm any ongoing costs before you commit.

AI use-case, model and risk map

We choose the AI use case and model against a real business workflow, not a novelty prompt.

Prompt, tool and retrieval design

GPT, Claude, Gemini, Azure AI, Llama, Mistral, Cohere, DeepSeek, Grok or Bedrock-hosted models can be considered when they fit the task.

System integration and logging

Prompting, retrieval, tools and logging are designed around the systems already in use.

Evaluation, handover and support notes

The integration keeps sensitive steps reviewable and makes AI outputs traceable where it matters.

What to check before you buy

Project start

Start with the business job

An AI Integration engagement starts by confirming what needs to change, who uses it, what can break and how it will be supported after launch.

Handover

Ownership stays clear

Handover should include source access where relevant, owner notes, support expectations and known risks to monitor after launch.

Checks

Show the working

Ask for a recent support note, maintenance report, workflow map or before-and-after summary that shows the issue, the fix and the next step.

Next step

Agree the boundary first

A short discovery or review keeps the work grounded in the business problem, keeps the price affordable, and makes the first useful step clear.

AI integration questions

Practical questions about AI Integration for Australian businesses.

Which AI models can you integrate?

We can design integrations around major model options including GPT and OpenAI, Anthropic Claude, Google Gemini, Microsoft Azure AI, Meta Llama, Mistral, Cohere, DeepSeek, xAI Grok and Amazon Bedrock-hosted models. The right choice depends on the task, privacy needs, cost, latency, data location, tool support and how the output will be reviewed.

Can we use AI without staff pasting work into public chat tools?

Yes. A controlled integration can put AI inside an approved workflow with permissions, logging, source content and human review, instead of relying on unmanaged copy-and-paste.

What should be logged in an AI integration?

At minimum: the use case, user action, model or provider used, model response, source material, errors, cost signals and any human approval step required by the workflow.

Can AI be used inside a website or portal?

Yes. AI can support drafting, triage, search, summaries and guided answers when the boundaries, content sources and handover path are clear.