Enterprise AI Platform Enablement

Organisations across investment management, professional services, and industrial sectors partnered with ELab to select and implement enterprise AI platforms tailored to their specific needs. Through structured platform selection, security-integrated implementation, and comprehensive team enablement, clients achieved productive AI adoption within 2-4 weeks, with 80%+ team adoption rates and measurable productivity improvements.

Industry: Cross-Industry | Duration: 2-6 weeks | Services: Platform Selection, Implementation, Training

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Many organisations recognise the productivity potential of AI but struggle with fundamental questions: Which platform is right for us? How do we implement it securely? How do we get our team actually using it effectively? Without expert guidance, organisations often make costly mistakes - selecting the wrong platform, implementing without proper security controls, or failing to drive meaningful adoption.

Key Pain Points

• Platform Overwhelm: Multiple options (Claude, ChatGPT, Copilot, Gemini) with unclear differentiation and conflicting vendor claims
• Security Concerns: Uncertainty about data handling, retention policies, and compliance requirements for enterprise AI
• Integration Gaps: Need for SSO, document access, and workflow integration but unclear how to achieve it
• Adoption Failure Risk: Previous AI tool purchases sitting unused because teams don't know how to apply them effectively

Business Impact

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ELab delivers end-to-end enterprise AI platform enablement, from objective platform evaluation through to productive team adoption. Our platform-agnostic approach ensures clients get the right solution for their needs, not a vendor's preferred product.

Phase 1: Platform Selection & Advisory

• Requirements gathering across security, integration, capability, and cost dimensions
• Hands-on evaluation of shortlisted platforms against client-specific criteria
• Proof-of-concept testing with real client use cases
• Clear recommendation with total cost of ownership analysis
• Vendor negotiation support where applicable

Phase 2: Implementation & Integration

• Platform provisioning and enterprise configuration
• SSO integration (Azure AD, Okta, Google Workspace)
• Security controls and data governance setup
• Document and knowledge base integration where supported
• Custom AI agent/coworker configuration for priority use cases

Phase 3: Training & Enablement

• Executive AI fundamentals session (use cases, governance, expectations)
• Team-specific training by role and function
• Prompt engineering workshops with hands-on practice
• AI champion identification and advanced training
• Ongoing support during adoption period

Platforms Implemented

ELab has production implementation experience across all major enterprise AI platforms:

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Quantitative Outcomes

Targeted Value

• Productivity Gains: Typically 2-5 hours per person per week targeted once adoption matures
• Cost Avoidance: Potential to prevent wrong platform selection (avoiding $10-50k in licensing mistakes)
• Risk Mitigation: Proper security configuration reducing potential compliance issues

Qualitative Benefits

Risk Reduction

• Platform Risk: Objective evaluation prevents costly wrong-platform decisions
• Security Risk: Enterprise-grade implementation with proper controls from day one
• Compliance Risk: Data handling and retention configured to meet regulatory requirements
• Shadow AI Risk: Sanctioned platform reduces uncontrolled personal tool usage

Operational Excellence

• Standardisation: Consistent AI tooling across the organisation
• Integration: AI accessible within existing workflows (Teams, Slack, email)
• Governance: Clear policies and usage guidelines from the start

Team & Culture

• Confidence: Teams trained to use AI effectively, not just access it
• Champion Network: Internal AI champions identified and equipped to support peers
• Culture Shift: AI becomes normalised productivity tool, not intimidating technology

Strategic Value

• Foundation: Platform implementation creates foundation for advanced AI initiatives
• Scalability: Enterprise platforms scale with organisation growth
• Future-Ready: Proper setup enables future integrations and expansions

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Implementation Examples

Stoneview Capital (Investment Management)

• Context: Commercial property investment firm needing AI-integrated CRM and investor relations
• Platform: Claude for Teams with custom CRM integration
• Outcome: Full CRM transformation with AI-enabled workflows
• Key Success Factor: Custom Claude skill development for CRM access

Compatico (Professional Services)

• Context: Growing firm needing AI to scale content and client delivery
• Platform: Enterprise AI with custom agent configuration
• Outcome: Targeted 66% reduction in content creation time, knowledge base captured
• Key Success Factor: Clear use-case prioritisation and hands-on training

Quantum (Industrial Operations)

• Context: Multi-site operator needing procedure access and knowledge management
• Platform: Enterprise AI integrated with Microsoft Teams
• Outcome: Targeted 2,700 hours annual time savings, 90% faster information retrieval
• Key Success Factor: Integration with existing tools (Teams) for frictionless adoption

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Enterprise AI platform implementation is typically the first step in a broader AI enablement journey. Once the foundation is established, organisations can build upon it with specialised AI agents, workflow automations, and advanced integrations.

Common Next Steps:

• Custom AI agent development for specific business processes
• Knowledge base expansion and optimisation
• Advanced integration with business systems (CRM, ERP)
• AI champion programme formalisation
• Managed AI services for ongoing optimisation

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• AI Foundations Workshop
• AI Readiness Assessment
• Strategic AI Roadmap
• AI Policy & Governance
• Pilot Implementation
• AI Coworker Deployment
• Managed AI Services
• vCAIO Advisory

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Platform Selection Criteria

We evaluate platforms across these dimensions to ensure the right fit:

For detailed platform capabilities, see Platform Capabilities Reference document.

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Document Control: v1.0 | Last Updated: February 2026 | Author: ELab

For more information, contact ELab at hello@elab.co.nz or visit www.elab.co.nz