Consulting
Practical AI adoption for high-consequence operations
MineGuard AI Consulting helps heavy-industry teams move from "AI interest" to safe, governed, measurable deployment—without slowing operations or compromising compliance. We combine app-building capability with site credibility: we understand how work really happens on the floor, what supervisors will (and won't) adopt, and what leaders need for defensibility.
What we're most experienced at
1. Change management for applying AI tools in heavy-industry
AI doesn't fail because the model is weak—it fails because:
- • workflows aren't clearly defined
- • permissions and accountability are unclear
- • frontline trust is low
- • "pilot outputs" aren't production-safe
- • governance & auditability aren't designed in
We specialise in getting adoption to stick: clear operating rhythms, training that matches shift reality, and guardrails that make AI usable in safety-critical environments.
2. Building high-quality, workflow-native apps (not demos)
We can deliver:
- • purpose-built tools (web and mobile)
- • structured outputs that match your templates and standards
- • integrations into your existing ecosystem
- • audit trails and evidence linking from day one
3. AI governance + strategy with applied experience
We help you define a governance model that is useful, not theoretical:
- • who can deploy what
- • which decisions must remain human
- • what must be logged
- • what data is allowed
- • what "good" looks like (quality + defensibility)
What else we can do
Our consulting service lines to accelerate safe AI adoption.
AI Strategy and Roadmapping
Heavy-industry focused:
- Identify the highest-value AI use cases (safety, reliability, operations, compliance)
- Prioritise based on risk, effort, and readiness (not hype)
- Define the target operating model: roles, skills, tooling, vendors, and internal ownership
Deliverables: Use-case portfolio, 90-day plan, 12-month roadmap, investment case.
Governance, Risk and Assurance
AI you can defend:
- AI policy that fits operational reality (not generic corporate policy)
- Human-in-the-loop decision boundaries for safety-critical work
- Logging and audit trail requirements (who/what/when/why)
- Prompt and content governance (versioning, approvals, change control)
- Privacy, security, data sovereignty and retention controls aligned to your risk profile
Deliverables: AI governance playbook, RACI, assurance checklist, audit-ready controls.
Data Readiness + RAG Knowledge Bases
- “What should be in the knowledge base?” and what should never be
- Document control, metadata strategy, and chunking aligned to your workflows
- Compliance-style retrieval: citations, traceability, and defensible outputs
- Quality scoring of your document set (gaps, contradictions, outdated content)
Deliverables: RAG blueprint, taxonomy/metadata spec, ingestion rules, quality report.
Safety Workflows Transformation
We redesign and implement AI-assisted workflows for:
- incident investigations (evidence-to-report with traceability)
- action management and learning capture
- critical control management and verification quality
- SHMS compliance and cross-document consistency checks
- frontline “how do I do this safely?” assistance
Deliverables: Future-state workflows, templates, tool configuration, rollout plan.
Implementation and Integration
Make it real in your ecosystem:
- Integrate with DMS and evidence repositories (controlled docs, photos, records)
- Identity and access management (SSO/MFA patterns where required)
- Role-based access and separation for site vs corporate visibility
- Build dashboards that leaders actually use (quality, cycle time, adoption, value)
Deliverables: Integration design, configuration, deployment runbooks, dashboards spec.
Training, Enablement and Adoption
- Supervisor/OCE/leadership training designed for shift time constraints
- “How to use AI safely” playbooks (what to trust, what to verify, when to stop)
- Prompting standards for consistent outcomes
- Train-the-trainer model for internal capability build
Deliverables: Training pack, user guides, quick reference cards, comms kit.
Vendor / Model Selection Support
Model-agnostic evaluation:
- Compare options (enterprise platforms vs specialist tools vs bespoke builds)
- Define evaluation criteria: safety, auditability, cost, retention, latency, UX
- Run controlled trials with measurable success criteria
Deliverables: Vendor scorecard, trial design, recommendation and rollout approach.
How we work
Step 1 — Discovery Sprint
(2–4 weeks)
- • map your highest-risk/high-value workflows
- • map your current evidence/document reality
- • map governance constraints you must satisfy
- • map the adoption barriers you'll face
Step 2 — Pilot with Guardrails
(4–8 weeks)
- • clear success metrics
- • strict boundaries on where AI can & cannot be used
- • quality gates and human verification steps
- • audit trail design from day one
Step 3 — Scale and Embed
(Ongoing / staged)
- • operationalise operating rhythm (training, QA, reviews)
- • roll out reporting and dashboards
- • continuous improvement (prompt/version control, feedback loop)
Typical outcomes clients look for
- Faster delivery of safety outputs without lowering quality
- Better consistency across sites (templates, definitions, expectations)
- Stronger defensibility: traceability, citations, and evidence linking
- Reduced admin load on safety/tech services teams
- Clear governance and risk controls for AI deployment
- Higher frontline engagement because tools actually fit the job
Why MineGuard AI?
- We build and deploy — we're not only advisors.
- Operational credibility — we design for real-world constraints: shift work, connectivity, time pressure, mixed capability.
- Safety + compliance first — audit trails, verification steps, and controlled outputs are built in.
- Heavy-industry language — we align to safety management systems, critical control thinking, and investigation rigor.
- Pragmatic architecture — right-sized solutions that don't assume a perfect enterprise stack.
Engagement Options (examples)
AI Adoption & Governance Sprint
strategy + governance + priority roadmap
Investigation Workflow Acceleration
quality + cycle time + defensibility
Critical Control Management Uplift
verification quality, standards, assurance
SHMS Compliance & Consistency
gap detection, clause mapping, document quality
Build-with-You App Delivery
co-design, build, rollout, train-the-trainer
Start your AI adoption correctly
If you want AI that your site teams will actually use—and your leaders can defend—we'll help you design it, deploy it, and make it stick.