Project Roadmap & Execution Plan

Comprehensive implementation strategy covering team structure, timeline, budget, risk management, and success metrics for NexStellar deployment

1

Team Structure & Scaling Plan

Strategic hiring plan to scale from proven solo execution to full government-scale team. Phased recruitment ensures knowledge transfer while maintaining quality and reducing risk.

Technical Team 15-20 personnel
AI Engineers 3-4
Backend Engineers 4-5
DevOps Engineers 2-3
QA Engineers 2-3
Data Engineers 3-4
Project Management 3-4 personnel
Project Manager 1
Business Analysts 1-2
Coordinators 1
Operations 5-8 personnel
Support Team 3-4
Training Team 1-2
Documentation 1-2
Leadership 3 personnel
CEO/CTO (Founder) 1
COO 1
CFO 1

Hiring Timeline

Month 1-3: Core team (5-8 people) - AI lead, Backend lead, PM, DevOps
Month 4-6: Scale to 15 - Complete technical team, add QA and support
Month 7-12: Full team (25-30) - Operations, documentation, expanded support
2

Detailed Timeline & Milestones

18-month implementation with parallel workstreams. Proven infrastructure allows aggressive timeline while maintaining quality.

Phase 1: Sovereign AI Development

Month 1
GPU Procurement & Infrastructure Setup
  • Acquire GPU cluster (8x NVIDIA A100)
  • Datacenter rack space setup
  • Network configuration and security
  • Development environment provisioning
Month 2
Team Recruitment & Dataset Preparation
  • Hire AI engineers and data scientists
  • Collect Malaysian government dataset
  • Data cleaning and annotation
  • Security clearance processing
Months 3-4
Dataset Preparation & Model Training Setup
  • Finalize training dataset (government context)
  • Setup training pipeline
  • Baseline Llama 3 70B evaluation
  • Define fine-tuning parameters
Months 5-6
Fine-tuning & Model Validation
  • Fine-tune Llama 3 70B on Malaysian data
  • Model evaluation and benchmarking
  • Optimize inference performance
  • Deploy model to production GPU cluster
✓ Milestone 1: Working sovereign AI model

Phase 2: Data Infrastructure (Parallel)

Months 4-5
Crawler Adaptation & Integration
  • Adapt NestDaddy crawler for government use
  • Document extraction (PDF, Excel, Word)
  • API integration with 3 pilot agencies
  • Security and authorization framework
Months 6-7
Pilot Agency Integration
  • Immigration Department integration
  • Ministry of Finance integration
  • Ministry of Health integration
  • Initial data extraction and indexing
Months 8-9
Scale to 10 Agencies
  • Expand to 7 additional agencies
  • Optimize crawler performance
  • Data lake expansion
  • Elasticsearch cluster scaling
Month 10
Full 23 Agency Deployment
  • Connect remaining 13 agencies
  • Complete data extraction pipeline
  • Index consolidation and verification
  • Performance optimization
✓ Milestone 2: All agencies connected

Phase 3: Intelligence Layer (Parallel)

Months 8-9
Query Parser & AI Integration
  • Natural language query parser development
  • AI model integration with search engines
  • Result interpretation and formatting
  • Pattern detection algorithms
Months 10-11
Dashboard & Visualization
  • Intelligence dashboard development
  • Data visualization components
  • Report generation engine
  • Alert and notification system
Month 12
Integration Testing & UAT
  • End-to-end integration testing
  • User acceptance testing with government users
  • Performance optimization
  • Security audit and penetration testing
✓ Milestone 3: Complete platform ready

Phase 4: Deployment & Scale

Months 12-14
Pilot Deployment (500 Users)
  • Deploy to pilot user group
  • Training sessions for government analysts
  • Gather feedback and iterate
  • Performance monitoring and optimization
Months 15-16
Scale to 2000 Users
  • Infrastructure scaling
  • Expanded training programs
  • Support team onboarding
  • Documentation finalization
Months 17-18
Full Production Deployment
  • Open to all authorized government users
  • 24/7 support operations
  • Continuous monitoring and optimization
  • Knowledge transfer to operations team
✓ Milestone 4: Production system live
3

Budget Breakdown

Detailed cost structure with transparent allocation across hardware, software, and human resources. Total investment: RM100M over 18 months.

Category Description Amount (RM)
CAPEX: Hardware & Infrastructure 30,000,000
GPU Cluster 8x NVIDIA A100 (80GB) for AI training/inference 15,000,000
Database Servers PostgreSQL cluster (5 nodes, high-availability) 5,000,000
Storage Infrastructure 1PB NVMe SSD + backup systems 3,000,000
Networking Equipment 10Gbps switches, load balancers, firewalls 2,000,000
Datacenter Setup Rack space, cooling, power, physical security 5,000,000
CAPEX: Software & Licenses 5,000,000
Enterprise Databases PostgreSQL enterprise support, Elasticsearch license 2,000,000
Development Tools IDEs, CI/CD tools, monitoring platforms 1,000,000
Security Software Firewalls, encryption, SIEM, vulnerability scanning 2,000,000
CAPEX: Development 25,000,000
Team Salaries (Year 1) 25-30 personnel average RM50K/month 15,000,000
AI Fine-tuning Compute costs, dataset preparation, expert consultants 5,000,000
Integration Costs Agency onboarding, API development, testing 5,000,000
OPEX: Operations (3 years) 20,000,000
Infrastructure Maintenance Datacenter, hardware maintenance, electricity 8,000,000
Operations Team Support, monitoring, incident response 8,000,000
Software Updates License renewals, security patches, upgrades 4,000,000
OPEX: Support & Training 10,000,000
User Training Training sessions, materials, workshops 4,000,000
Documentation User manuals, API docs, technical guides 2,000,000
24/7 Support Helpdesk, escalation, user assistance 4,000,000
OPEX: Enhancements 10,000,000
Feature Development New capabilities based on user feedback 6,000,000
Performance Optimization Ongoing improvements, scaling adjustments 2,000,000
Security Audits Penetration testing, compliance reviews 2,000,000
TOTAL PROJECT COST 100,000,000
4

Risk Management Framework

Proactive risk identification with concrete mitigation strategies. Proven infrastructure and phased rollout minimize technical and operational risks.

Technical Risks
AI Accuracy Issues
Mitigation: Human-in-loop validation, confidence thresholds, continuous retraining
Data Quality Problems
Mitigation: Automated validation pipelines, data cleansing, quality metrics dashboard
Scalability Bottlenecks
Mitigation: Proven with 4.9M docs, horizontal scaling architecture, load testing
Integration Failures
Mitigation: Phased rollout (3 pilot agencies first), comprehensive API testing, fallback mechanisms
Operational Risks
Team Recruitment Delays
Mitigation: Partner with universities (UPNM, UKM), MDEC support, competitive salaries
Agency Cooperation Issues
Mitigation: Board member connections, official government mandate, dedicated liaison officers
Budget Overruns
Mitigation: Fixed-price milestones, proven infrastructure reduces unknowns, 10% contingency
Knowledge Transfer
Mitigation: Comprehensive documentation, training programs, operations runbooks
Strategic Risks
Vendor Lock-in Concerns
Mitigation: Open-source stack (Llama 3, PostgreSQL), on-premise deployment, full source code access
Political Changes
Mitigation: Multi-party board, positioned as national asset, long-term contracts
Technology Obsolescence
Mitigation: Modular architecture, upgrade path planned, continuous R&D allocation
Security Breaches
Mitigation: Defense-in-depth security, regular audits, ISO 27001 compliance, incident response plan
5

Success Metrics & KPIs

Measurable success criteria across performance, business value, and technical excellence. Clear targets enable objective evaluation and continuous improvement.

Performance Metrics
Query Response Time
< 2 seconds
95th percentile for complex queries
System Uptime
99.5%
Maximum 43 hours downtime per year
Data Freshness
< 24 hours
From source update to indexed
Concurrent Users
5000+
Simultaneous active users supported
Business Metrics
Cost Savings
RM 50M/year
vs manual analysis and reporting
Decision Speed
10x faster
Intelligence retrieval and analysis
Fraud Detection
+30%
Improvement in anomaly identification
User Satisfaction
> 80%
Positive feedback from government users
Technical Metrics
Data Indexed
1B+ records
By Year 2 of operations
Agencies Connected
23 agencies
Within 12 months deployment
AI Accuracy
> 90%
On standard NLP benchmarks
API Availability
99.9%
For agency integrations
6

Compliance & Certification Framework

Comprehensive certification roadmap ensuring government-grade security, quality, and operational standards. Certifications achieved as project milestones.

Security Certifications
ISO 27001 (Information Security) Month 12
PDPA Compliance (Data Protection) Month 6
Government Security Clearance Month 3
Penetration Testing Reports Quarterly
Quality Certifications
ISO 9001 (Quality Management) Month 12
CMMI Level 3+ (Capability Maturity) Month 18
Agile/Scrum Certifications Ongoing
ITIL Service Management Month 15
Infrastructure Certifications
TIER III Datacenter Month 3
Disaster Recovery Tested Month 9
Business Continuity Plan Month 6
SOC 2 Type II Compliance Month 18
7

Project Deliverables

Comprehensive list of tangible outputs delivered at each project phase. All deliverables include documentation, training, and knowledge transfer.

Phase 1: Sovereign AI
AI Model & Infrastructure
  • Fine-tuned Llama 3 70B model (Malaysian context)
  • GPU cluster fully operational
  • Model inference API documentation
  • Benchmark performance reports
  • Training dataset documentation
  • AI ethics and bias audit report
Phase 2: Data Infrastructure
Crawler & Data Pipeline
  • Production crawler (200K+ docs/day capacity)
  • 23 agency integrations complete
  • Data lake with 1B+ records indexed
  • Elasticsearch cluster deployed
  • API documentation for agency access
  • Data quality monitoring dashboard
Phase 3: Intelligence Layer
Platform & Analytics
  • Intelligence dashboard (web application)
  • Natural language query interface
  • Report generation engine
  • Alert and notification system
  • Data visualization components
  • User permission and RBAC system
Phase 4: Deployment
Production System
  • Fully operational production environment
  • 24/7 support operations
  • User training materials and workshops
  • Operations runbooks and procedures
  • Disaster recovery plan tested
  • Knowledge transfer sessions complete
Documentation
Comprehensive Documentation
  • System architecture documentation
  • API reference guides
  • User manuals (Bahasa & English)
  • Administrator guides
  • Security and compliance reports
  • Source code with inline documentation
Support & Training
Ongoing Support
  • Training for 2000+ government users
  • Helpdesk and support ticketing system
  • Monthly performance reports
  • Quarterly security audits
  • Annual penetration testing
  • Continuous system optimization

Proven Execution. National Impact.

NexStellar combines proven technical infrastructure with comprehensive execution planning. From team structure to compliance certifications, every aspect is designed for government-scale deployment and long-term sustainability.

Beyond V1: Strategic Evolution Plan

After V1 proves ROI, NexStellar 2.0 adds world-class capabilities: Graph Analysis, Workflow Automation, Mobile Operations, and more. Elevate to full Palantir-level sophistication while maintaining sovereignty.

View Evolution Roadmap →