Practical AI consulting for Australian SMEs

Salt Grain offers AI consulting for SME Australia and mid-market teams who want AI to do something useful on Monday — not a transformation slogan. If you are drowning in repetitive decisions, or sitting on data that never becomes action, you’re the audience.

Good fit:

• High volume of patterned work (triage, classifying, drafting, checking)
• Reports exist; decision-ready insight is slow
• You want a pilot with clear success criteria before scale
• You already run CRM/ERP/work tools and need AI inside them

Not a fit: hype tours, model research for its own sake, or “AI strategy” with no build path.

AI theatre creates demos. Operations need workflows. Risks include shadow tools, unclear data handling, and automations nobody owns.

We focus on:

• Repetitive decisions that burn senior time
• Manual handoffs that could be assisted or automated safely
• Knowledge trapped in inboxes and PDFs
• Pilot ideas with no integration to real systems

Practical AI means scoped builds, governance, and measurement — in your stack.

We don’t sell an AI platform. We embed intelligence where work already happens.

• Strategy filter — only use cases that move a business metric or remove clear waste
• CX lens — customer-facing automation must match the service you intend to deliver
• Systems first — CRM, ERP, monday.com, Workato, web — AI as a layer, not a parallel universe
• Delivery — build, enable, monitor. Your team owns the workflow

Anti-hype is the point. If a simpler automation beats a model, we say so.

• Listen — Map candidate use cases, data realities, risk and ownership.
• Shape — Pick one or two pilots with success metrics, human-in-the-loop rules, and stack fit.
• Build — Implement inside existing tools where possible; integrate with Workato or APIs when needed.
• Deliver — Production hardening, training, monitoring. Expand only after first value.

Cost conversations stay qualitative until scoped: think fixed-scope pilots measured in weeks, not open-ended “AI transformation” retainers. Exact bands depend on complexity and data readiness — sized in discovery.

Practical AI for Australian SMEs still needs adult supervision:

• Human-in-the-loop where mistakes hurt customers or compliance
• Clear data boundaries — what leaves your environment, what stays
• Ownership — named workflow owner, not “the AI did it”
• Rollback — ability to disable a pilot without freezing the business
• Measurement — time saved, error rate, customer impact — agreed before build

We will decline use cases that are mostly surveillance, dark patterns, or unexplained automated decisions in sensitive contexts. Anti-hype includes ethics, not only ROI slides.

If your biggest opportunity is actually process redesign, we route you to service design first — models on a broken journey just accelerate the mess.

Patterns we see work for SMEs and mid-market teams in Australia:

• Inbox and ticket triage with human review on edge cases
• Drafting assistance for proposals, summaries and knowledge answers
• Classification of leads, cases or documents into existing CRM/ERP fields
• Assisted routing across teams without removing accountability

We avoid “chat with all company data” as a day-one ambition. Narrow, measurable, reversible — then expand.

Public SME AI guides often talk in fixed-scope pilot bands rather than open-ended retainers. We work the same way: define the workflow, the success metric, and the boundary conditions, then price the build. Exact figures depend on data readiness, integrations and review requirements — discovery first, no fantasy fixed price from a contact form.