Choose the AI platform around the work it must support.
Define the architecture and delivery path before implementation.
We assess the priority use case, knowledge and data readiness, security policies, existing systems, and operating responsibilities. We then compare Snowflake, cloud AI, and on-premises options to define the platform approach, target architecture, and delivery roadmap.
A product comparison alone does not define the implementation scope
The same platform may fit one workflow but not another because data location, security policies, existing systems, and operating responsibilities differ. Choosing a product first can mean that the required knowledge and data are not ready—or that the operating model must be redesigned after the proof of concept.
Target Workflow & Human Responsibility
Define where AI will support analysis, search, reporting, recommendations, and approval workflows, and which decisions remain under human authority.
Knowledge & Data Requirements
Identify the required data, documents, business rules, and expert knowledge, including where they reside and the requirements for quality and freshness.
Deployment Constraints
Use data-transfer restrictions, network segmentation, privacy, and confidentiality policies to assess cloud, on-premises, and hybrid options.
Operating Ownership & Control
Define who will manage models, knowledge, agents, permissions, costs, and changes, and establish the required review and approval procedures.
Move from use-case selection to a target architecture and delivery roadmap
Use Case Discovery
Identify candidate workflows from the AI transformation strategy and business priorities, then assess their business value, feasibility, risks, and implementation priority.
Readiness Assessment
Document the current readiness of business rules, knowledge, data, technology, organizational roles, and governance controls, then identify gaps to address before implementation.
Platform Assessment
Apply a common evaluation framework to Snowflake, cloud AI services, commercial AI platforms available in Korea, and open-source configurations.
Target Architecture
Define where knowledge, data, models, agents, applications, and AgentOps components reside, the role of each component, and how they integrate.
Operating Model
Define business and IT responsibilities and the criteria for human review, permissions, evaluation, deployment, and change management.
Delivery Roadmap
Define the questions to test in the proof of concept, the implementation and transition scope, cost and schedule assumptions, the work required for operational readiness, and the sequence for expansion.
Compare fit in the operating environment—not feature counts
We define validation questions around actual workflows and client data rather than relying on proposal checklists. The comparison also considers the integrations, operating effort, and cost required after adoption.
Business & Workflow Fit
Assess accuracy and response-time requirements, approval and exception-handling needs, user-interface requirements, and fit with existing business processes.
Knowledge & Data Fit
Assess requirements for structured and unstructured data, the Semantic Layer, search, and the Knowledge Graph, together with data freshness, quality, and source traceability.
Security & Governance
Review data-location and transfer restrictions, access controls, requirements for personal and confidential data, model-training and logging policies, and audit requirements.
Integration & Architecture
Review ERP and business systems, Snowflake and other data platforms, APIs and tools, and where models and applications will run.
Model & Platform Flexibility
Assess model choice by workflow, replacement and extension options, platform dependencies, and the ability to adapt as technology changes.
Cost & Operability
Consider licenses, usage, infrastructure, implementation and operating staff, monitoring, and technical support when estimating total cost and operating complexity.
Choose the deployment model based on security and operating constraints
The deployment model determines more than infrastructure. It also defines where data and knowledge reside, where models run, which tools agents can use, how logs are handled, and who is responsible for each part of the environment.
Snowflake-Centered Cloud
When cloud use is permitted and the relevant data is in Snowflake, assess an architecture that can reduce the need for separate copies and integrations.
Restricted-Network & On-Premises Environments
When data transfer is restricted, compare commercial AI platforms available in Korea with open-source options for models, search, and knowledge retrieval, based on the client’s infrastructure and operating requirements.
Hybrid
A hybrid design can keep sensitive data and internal workflows in the client environment while placing permitted data and AI capabilities in the cloud, with clear responsibility and control boundaries.
End the assessment with the decisions needed to proceed
Priority Use Case & Boundaries
Record the first implementation target and exclusions, expected business value and risks, and the criteria for evaluating success.
Readiness Gaps
List the gaps in business rules, knowledge, data, security, and organizational readiness that should be addressed before implementation.
Platform Decision & Target Architecture
Document the selected platform approach and rationale, the role of each component, data flows, and integrations with existing systems.
Proof of Concept & Delivery Roadmap
Record the proof-of-concept validation plan, phased delivery sequence, cost and schedule assumptions, operational transition plan, and expansion path.
Use AI to structure the evidence, then verify findings against source material
AI can analyze AI transformation strategies, business documents and processes, data models, system diagrams, security policies, interview notes, and candidate platform documentation. It can prepare structured requirements and comparison drafts. Consultants verify the findings against source documents and technical evidence, while conflicting or unconfirmed information remains explicitly tracked as open questions.
Source Analysis
Identify business requirements, data and system dependencies, and security and operating constraints in the available materials.
Requirements Structuring
Organize requirements from different documents and stakeholder groups into comparable criteria and priorities.
Criteria Drafting
Translate business and technical requirements into draft criteria and validation questions for each candidate.
Candidate Comparison
Compare how each option meets the criteria, including gaps, assumptions, and areas that require further validation.
Evidence & Open Questions
Verify assessment findings against source documents and technical materials, and track conflicting or unconfirmed information separately.
Start with the use case and platform options under consideration
Tell us about the target workflow, candidate platforms, data environment, security policies, any prior proof-of-concept work, and the planned operating model. We will help define the assessment scope and priority questions.
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