Helping organizations move AI initiatives from experimental pilots to scalable, governed, and business-ready systems.
THE CONTEXT
Strategic Advisory for Post-LLM Implementation
While many organizations have initiated LLM adoption, the true complexities often emerge after the pilot phase.
CODEICX assists enterprises in navigating architectural opacity, governance risks, and scalability bottlenecks—ensuring that LLMs are not just functional, but secure, scalable, and value-driven for the long term.
We provide Second-line Professional Advisory to complement your existing teams, ensuring your LLM infrastructure is built correctly and maintained with stability.
ENGAGEMENT
Who This Is For
Our advisory is tailored for organizations that:
- Have integrated LLMs into active business processes.
- Possess successful PoCs but face challenges scaling across departments.
- Are encountering mounting pressures regarding costs, security, or compliance.
- Require an independent third-party perspective to audit internal blind spots.
METHODOLOGY
Our Service Approach
Phase I
Post-Implementation Review
Comprehensive audit of existing LLM architecture:
- Prompt and data flow design review
- Model selection and utilization strategy
- Integration patterns and systemic dependencies
- Cybersecurity and compliance risk assessment
Phase II
Governance & Optimization
Establishing sustainable frameworks:
- Governable prompt and application architecture
- Cost-predictive model usage policies
- AI usage frameworks aligned with internal audits
- Design flexibility for future model migrations
Phase III
Customized LLM Roadmap
Transitioning from “functional” to “scalable”:
- Short-term Quick Wins for immediate correction
- Mid-term integration and optimization plans
- Long-term AI/LLM strategic blueprinting
Phase IV
Technical Support
- Drafting clear, actionable technical specifications
- Support in migrating from PoC to production rollout
- Coordination with dev teams to mitigate risks
Phase V
Knowledge Transfer
- Equipping teams with LLM best practices
- Building capacity for independent maintenance
- Reducing long-term dependency on vendors
CAPABILITIES
Application Scenarios
Internal Knowledge Base & Search
Customer Support LLM Integration
Automated Document Analysis
Internal Training & Content Gen
Compliance & Audit-Oriented AI Scenarios