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DELIVERY // ENGAGEMENT_ROLES

Clear roles on every engagement.

ROLE // 01

Engagement Lead

Owns the business outcome, executive relationship, and value case.

ROLE // 02

Solution Architect

Owns cloud, data, AI, and integration architecture.

ROLE // 03

Specialist Advisors

Provide deep expertise in governance, security, data, GenAI, or FinOps.

ROLE // 04

Delivery Support

Maintains momentum, documentation, coordination, and client experience.

Our promise You will always know who is accountable for your outcome.

FRAMEWORK // AI_TRUST_STACK

The AI Trust Stack™

Our shared delivery standard. Technology is only one layer. Trusted AI requires the right business case, data foundations, controls, oversight, and operating model.

Every engagement—from a discovery to a capability accelerator—is assessed against all eight layers, so nothing that blocks production is discovered late.

  1. 08
    Change management Adoption, enablement, and an operating model that lasts.
  2. 07
    Governance Policies, risk registers, and controls aligned to ISO/IEC 42001.
  3. 06
    Observability & FinOps Quality, latency, and cost visibility in production.
  4. 05
    Human oversight Defined review points, escalation paths, and accountability.
  5. 04
    Model risk Evaluation, failure modes, and fitness-for-purpose testing.
  6. 03
    Security Access control, boundary protection, and secure integration.
  7. 02
    Data quality Trusted, governed data foundations the model can rely on.
  8. 01
    Business value A clear value case and measurable outcome before any build.
FRAMEWORK // 90_DAY_SPRINT

The 90-Day AI Readiness Sprint™

A structured path from scattered AI ambition to a funded, defensible decision—delivered by our senior team alongside yours.

  1. Days 1–15

    Discover

    Business goals, constraints, risks, and current initiatives

  2. Days 16–30

    Prioritize

    High-value, feasible AI opportunities

  3. Days 31–50

    Design

    Architecture, governance, data, and delivery approach

  4. Days 51–75

    Validate

    Assumptions, controls, and production readiness

  5. Days 76–90

    Decide & mobilize

    A funded scale, pause, or redirect decision

PROOF // REPRESENTATIVE_ENGAGEMENTS

What this looks like in practice.

CASE // PILOT_TO_PRODUCTION

Enterprise leadership team

ChallengeA leadership team had multiple AI pilots but no trusted path to production.
ApproacheMota conducted a readiness assessment, prioritized use cases, and designed a governed delivery path.
OutcomeLeadership gained a clear investment decision, production-readiness controls, and a repeatable delivery model.
CASE // HEALTHCARE_VOICE_AI

Healthcare provider

ChallengeSurgical scheduling relied on manual inbound and outbound phone operations.
ApproachOur team designed and delivered agentic voice automation with EMR connectivity and compliance workflows.
OutcomeCall-handling cost reduced from ~$15 to under $0.01 per call (97% reduction) with a 70–80% automation rate.
View architecture
CASE // FINANCIAL_RISK_GENAI

Financial services

ChallengeUnderwriting depended on manual review of bank statements and financial documents.
ApproachWe architected a compliance-first GenAI risk assessment workflow that extracts and analyzes document data.
OutcomeReduced manual review effort and improved underwriting decisions through a governed, auditable workflow.
View architecture
SECURE_GATE // STRATEGY_CALL

See how our approach fits your priorities.

A focused conversation with our advisory team to understand your AI priorities, identify the real constraint, and determine whether a discovery or readiness engagement makes sense.

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