Maayan AI Consulting helps organizations move beyond “digital transformation” into AI-powered reinvention—where decisions are smarter, operations are faster, and customer experiences are more personalized and resilient. In today’s environment, AI and GenAI are not optional innovation projects; they are foundational capabilities that determine how quickly an enterprise can adapt, compete, and scale. Yet many organizations face the same challenges: fragmented data, siloed teams, unclear use cases, ungoverned experimentation, and pilots that never reach production.
Maayan Technologies addresses this gap by building Live Enterprises—organizations that are AI-powered, digitally agile, continuously learning, and resilient. Our AI consulting practice is designed to help leadership teams and delivery teams align on a clear AI vision, a practical roadmap, and a measurable execution plan. We combine strategy, engineering leadership, governance, and enablement to ensure your AI initiatives deliver real outcomes, not just prototypes.
Our consulting approach is grounded in five guiding principles:
- Outcome-first transformation: Every AI initiative is tied to business KPIs—revenue, cost, risk, productivity, quality, and customer satisfaction.
- AI-first data foundation: We modernize how data is collected, governed, secured, and exploited—so models and GenAI applications can perform reliably.
- Responsible AI by design: We embed security, privacy, auditability, and policy controls from day one to reduce risk and build trust.
- Pilot-to-scale execution: We help you move rapidly from experimentation to production with repeatable delivery patterns (MLOps/LLMOps).
- Capability building: We ensure your teams can operate and improve AI continuously through training, operating models, and Centers of Excellence (CoE).
Whether you are a mid-sized organization starting your AI journey or an enterprise scaling GenAI across functions, Maayan AI Consulting provides the clarity, structure, and execution support to make AI a sustainable competitive advantage.
We help organizations define how AI supports their long-term ambition. This includes:
AI vision aligned to the Live Enterprise model
Business value mapping across functions (Operations, Finance, Sales, HR, IT, Supply Chain, Customer Service)
Prioritized use-case portfolio with estimated ROI, complexity, and risk
Build vs buy decisions for models, platforms, and vendors
Data and platform roadmap (cloud, on-prem, hybrid)
Talent and operating model recommendations
Deliverable examples: AI Strategy Blueprint, Use-Case Portfolio, 12–18 month Roadmap, Budget & TCO model.
Before scaling AI, organizations must know what will block them. We assess:
Data availability, quality, lineage, and governance
Architecture readiness (data platform, integration layer, APIs, identity and access)
Security posture and compliance (privacy, data residency, sector regulations)
Current analytics/ML maturity, tools, and delivery processes
Skills maturity and organizational alignment
Deliverable examples: AI Readiness Scorecard, Gap Analysis, Risk Register, and Action Plan.
GenAI is transforming knowledge work, but without guardrails it can create operational and brand risk. We support:
GenAI use-case identification (enterprise search, copilots, customer support, internal assistants)
RAG (Retrieval-Augmented Generation) strategies and design
Agentic workflows (tool-using agents for approvals, ticket resolution, procurement actions, reporting)
Prompt management, evaluation frameworks, and safety controls
Security architecture for LLM access, data boundaries, and monitoring
Deliverable examples: GenAI Architecture, Guardrails Framework, Prompt & Evaluation Playbooks, Pilot-to-Scale Plan.
Trust is essential for enterprise AI adoption. Maayan provides governance that enables speed without losing control:
Responsible AI policy aligned to business and regulatory needs
Model risk management, approval workflows, and accountability roles
Bias testing and fairness assessments where relevant
Explainability requirements for high-stakes decisions
Audit trails, documentation templates, and compliance mapping
Data access controls and privacy-by-design controls
Deliverable examples: AI Governance Operating Model, Model Documentation Templates, Approval Workflow Design, Responsible AI Toolkit.
We design AI organizations that can scale delivery sustainably:
AI CoE model (centralized, federated, hybrid) based on organization structure
Roles and responsibilities (data owners, product owners, ML engineers, platform, security)
Intake process for new use cases and portfolio governance
Delivery standards (MLOps/LLMOps, testing, monitoring, change management)
Measurement system (value realization, adoption metrics, model performance)
Deliverable examples: CoE Charter, RACI, Delivery Playbooks, Training Plan, KPI Framework.
Many AI programs die at the “pilot” stage. Maayan helps convert pilots into production services:
Reference architectures and reusable patterns
MLOps/LLMOps pipeline design (CI/CD, monitoring, retraining, approvals)
Integration with enterprise systems (ERP, CRM, MES, Data warehouses)
Monitoring for drift, quality, and user feedback loops
Change management and user adoption planning
Deliverable examples: Production Readiness Checklist, Deployment Playbook, Monitoring Dashboards, Adoption Toolkit.
Maayan AI Consulting is designed for organizations that want outcomes fast, without sacrificing trust, security, or scalability.
We don’t treat AI as a side project. We design AI as a core operating capability:
AI-powered decisions: predictive insights, recommendations, and automated actions
Digital agility at scale: modern platforms and integration, rapid iteration
Always-on learning: feedback loops, continuous model improvements, workforce enablement
This creates a sustainable model where AI gets better over time and remains aligned to business priorities.
Many consulting firms deliver strategy, while engineering teams struggle to execute. Maayan bridges this gap by combining:
Business value mapping and domain alignment
Architecture and platform strategy
Engineering execution patterns and governance
Training and operational enablement
This reduces handoff risk and accelerates real-world implementation.
We make sure AI is safe and trustworthy:
Guardrails for GenAI (data boundaries, hallucination checks, citations, escalation)
Auditability for high-impact decisions
Security-first architecture for enterprise data and models
Clear accountability and model lifecycle controls
This builds confidence with leadership, compliance teams, and end users.
Maayan uses reusable frameworks and templates to deliver faster:
Use-case prioritization framework (value, feasibility, risk)
Reference architectures (GenAI, ML, hybrid deployment)
Evaluation templates for model quality and GenAI responses
CoE and governance toolkits
Production readiness checklists and monitoring standards
This shortens time-to-value and ensures consistency.
Even strong AI systems fail if users don’t trust them. We drive adoption through:
Human-in-the-loop design for sensitive workflows
Clear “what the model can and can’t do” communication
Training, change management, and operational playbooks
Success metrics tied to business outcomes and user usage
Maayan AI Consulting is measured by tangible improvements—not activity metrics. Typical outcomes include:
A clear AI roadmap with prioritization, timeline, and investment plan
Reduced uncertainty for leadership through validated use-case business cases
Alignment across business, IT, security, and operations teams
Faster cycle times via automation and agentic workflows
Reduced manual workload in processing, triage, approvals, and reporting
Better decision-making with predictive analytics and real-time insights
Improved ROI through focused use cases and proper scaling approach
Lower cost of experimentation through shared platforms and governance
Higher productivity (more output per employee) through copilots and automation
Reduced AI risk through governance, policy, and monitoring
Compliance-ready documentation and audit trails
Better security posture for data and AI systems
Data foundation improvements: quality, availability, governance, access control
Production-grade MLOps/LLMOps pipelines for reliable deployment
Higher stability and trust due to monitoring, drift detection, and evaluation systems
Maayan AI Consulting is designed for organizations that want outcomes fast, without sacrificing trust, security, or scalability.
At Maayan Tech, we are committed to providing exceptional service and support. Your questions, feedback, and inquiries are important to us, and we will do our best to respond promptly. Whether you’re a business seeking technology solutions or an individual with a query, we are here to assist you.
