Roadmap & Development Plan
Expert Fabric's development roadmap is structured in three phases, each building on the previous to create a comprehensive platform that scales from MVP to global AI-human collaboration network.
Development Phases
Phase 1: MVP Foundation (Q2-Q3 2025)
Timeline: 6 months
Investment: $2M
Team: 12-15 engineers
Core Platform Development
Task Orchestration Engine
- Basic task decomposition using LLM analysis
- Simple expert node assignment algorithm
- Core workflow management with status tracking
- RESTful API for task submission and monitoring
Expert Node Framework
- AI expert nodes for common tasks (document analysis, code generation, data processing)
- Human expert onboarding and management system
- Basic MCP integration for tool access
- Simple compensation tracking and payout system
Knowledge Management
- Vector database for task and expert embeddings
- Basic RAG implementation for context retrieval
- Simple knowledge capture from completed tasks
- Client data isolation and privacy controls
User Interface
- Web application for task submission and monitoring
- Basic expert dashboard for human contributors
- Administrative console for platform management
- Real-time status updates and notifications
Target Capabilities
- Task Types: Financial analysis, code review, document summarization, research synthesis
- Expert Pool: 50 verified human experts across finance, technology, and research domains
- Processing Capacity: 100 tasks per month
- Response Time: 4-24 hours for most tasks
Success Metrics
- Pilot Customers: 3 enterprise clients
- Task Completion Rate: 95%+
- Quality Score: 4.2/5.0 average client rating
- Expert Utilization: 60% average across expert pool
- Platform Uptime: 99.5%
Phase 2: Scale & Enterprise (Q4 2025 - Q2 2026)
Timeline: 9 months
Investment: $5M
Team: 25-30 engineers
Platform Enhancement
Advanced Orchestration
- Machine learning-powered task decomposition
- Dynamic expert assignment with performance optimization
- Multi-stage workflows with dependency management
- Advanced quality assurance with automated validation
Enterprise Features
- SOC 2 Type II compliance certification
- Advanced RBAC with custom role definitions
- On-premises deployment options
- Enterprise SSO integration (SAML, OIDC)
- Advanced audit logging and compliance reporting
Expert Marketplace
- Third-party expert node SDK and marketplace
- Expert performance analytics and optimization
- Dynamic pricing based on demand and quality
- Expert community features and collaboration tools
API & Integration Platform
- GraphQL API with advanced querying capabilities
- Webhook system for real-time integrations
- Pre-built connectors for popular enterprise tools
- Custom workflow template creation and sharing
Advanced Capabilities
- Task Types: Legal document review, technical architecture design, market research, content creation
- Expert Pool: 500+ experts across 20+ domains
- Processing Capacity: 2,000 tasks per month
- Response Time: 1-8 hours for most tasks
Technical Infrastructure
Success Metrics
- Enterprise Customers: 15 paying enterprise clients
- Monthly Revenue: $500K
- Task Volume: 2,000+ tasks per month
- Expert Network: 500+ active experts
- Platform Availability: 99.9%
- Customer NPS: 70+
Phase 3: Open Platform (H1 2026 - H2 2026)
Timeline: 12 months
Investment: $8M
Team: 40-50 engineers
Open Ecosystem Development
Decentralized Expert Network
- Blockchain-based reputation and compensation system
- Decentralized expert node deployment
- Cryptographic task assignment and verification
- Transparent micropayment distribution
AI Model Marketplace
- Support for multiple AI model providers
- Custom model fine-tuning and deployment
- Model performance benchmarking and optimization
- Community-contributed specialized models
Global Scaling Infrastructure
- Multi-region deployment with edge computing
- Advanced caching and CDN integration
- Elastic auto-scaling based on demand
- Global expert network with localization
Developer Ecosystem
- Open-source expert node framework
- Community marketplace for nodes and templates
- Developer certification and training programs
- Hackathons and innovation challenges
Platform Architecture Evolution
Advanced Capabilities
- Task Types: Any knowledge work that can be decomposed and distributed
- Expert Pool: 5,000+ experts globally across all domains
- Processing Capacity: 20,000+ tasks per month
- Response Time: Minutes to hours depending on complexity
Success Metrics
- Global Reach: Available in 50+ countries
- Annual Revenue: $50M run rate
- Expert Community: 5,000+ active experts
- Developer Ecosystem: 1,000+ custom nodes deployed
- Platform Transactions: 1M+ tasks completed annually
Technical Milestones
Q2 2025: MVP Launch
- Core orchestration engine deployed
- Basic expert node framework operational
- Vector database and RAG system functional
- Web interface for task submission
- 3 pilot customers onboarded
Q3 2025: Product-Market Fit
- 100 tasks successfully completed
- Quality metrics consistently above 4.0/5.0
- Expert pool expanded to 50 verified contributors
- Customer feedback loop established
- Basic analytics and reporting available
Q4 2025: Enterprise Ready
- SOC 2 compliance achieved
- Enterprise SSO integration complete
- On-premises deployment option available
- Advanced RBAC implementation
- 10 enterprise customers signed
Q1 2026: Scale Infrastructure
- Auto-scaling infrastructure deployed
- Multi-region availability
- GraphQL API with advanced features
- Expert marketplace beta launch
- 1,000 tasks per month capacity
Q2 2026: API Platform
- Public API generally available
- Webhook system operational
- Third-party integrations marketplace
- Custom workflow templates
- Developer documentation and SDKs
Q3 2026: Global Network
- Blockchain compensation system
- Decentralized expert nodes
- Global expert network operational
- Multi-language support
- Regional compliance frameworks
Risk Mitigation Strategies
Technical Risks
AI Model Dependency
- Risk: Over-reliance on specific AI providers
- Mitigation: Multi-provider abstraction layer, open-source model support
- Timeline: Implemented in Phase 2
Scalability Challenges
- Risk: Platform cannot handle rapid growth
- Mitigation: Cloud-native architecture, microservices design
- Timeline: Architecture decisions made in Phase 1
Security Vulnerabilities
- Risk: Data breaches or system compromises
- Mitigation: Security-first design, regular audits, compliance certification
- Timeline: Ongoing throughout all phases
Market Risks
Expert Supply Constraints
- Risk: Insufficient high-quality experts
- Mitigation: Competitive compensation, expert development programs, global recruitment
- Timeline: Continuous expert acquisition strategy
Customer Adoption Challenges
- Risk: Slow enterprise adoption
- Mitigation: Pilot programs, ROI demonstration, customer success team
- Timeline: Customer success focus from Phase 1
Competitive Response
- Risk: Large tech companies copying the model
- Mitigation: Patent portfolio, network effects, open platform strategy
- Timeline: IP protection strategy in Phase 1, network effects by Phase 2
Operational Risks
Regulatory Compliance
- Risk: Changing data privacy regulations
- Mitigation: Privacy-by-design, compliance automation, legal expertise
- Timeline: Compliance framework established in Phase 1
Quality Control at Scale
- Risk: Maintaining quality as volume increases
- Mitigation: Automated quality systems, expert training, continuous monitoring
- Timeline: Quality systems enhanced each phase
International Expansion
- Risk: Complexity of global operations
- Mitigation: Phased geographic expansion, local partnerships, regulatory expertise
- Timeline: International expansion begins Phase 3
Investment & Resource Requirements
Phase 1 Budget ($2M)
- Engineering Team: $1.2M (12 engineers × $100K avg)
- Infrastructure: $200K (cloud, tools, services)
- Expert Acquisition: $300K (recruitment, onboarding, initial compensation)
- Operations: $300K (legal, compliance, business development)
Phase 2 Budget ($5M)
- Engineering Team: $2.5M (25 engineers × $100K avg)
- Infrastructure: $800K (enterprise features, scaling)
- Expert Network: $1M (500 experts, marketplace development)
- Sales & Marketing: $500K (enterprise sales, customer success)
- Operations: $200K (legal, compliance, administration)
Phase 3 Budget ($8M)
- Engineering Team: $4M (40 engineers × $100K avg)
- Infrastructure: $1.5M (global deployment, blockchain)
- Expert Ecosystem: $1.5M (global expert network, developer programs)
- Sales & Marketing: $800K (global expansion, partnerships)
- Operations: $200K (international operations, compliance)
Total Investment: $15M over 18 months
Success Criteria & Exit Strategy
Short-term Success (12 months)
- Revenue: $3M annual run rate
- Customers: 15 enterprise clients
- Expert Network: 500+ active experts
- Platform Reliability: 99.9% uptime
- Quality Metrics: 4.5/5.0 average rating
Medium-term Success (24 months)
- Revenue: $25M annual run rate
- Market Position: Top 3 AI-human collaboration platform
- Global Presence: 20+ countries
- Expert Community: 2,000+ contributors
- Developer Ecosystem: 500+ custom nodes
Long-term Vision (36+ months)
- Market Leadership: Dominant platform for AI-human collaboration
- Revenue: $100M+ annual run rate
- Global Scale: 50+ countries, 10,000+ experts
- Platform Economy: Self-sustaining ecosystem with network effects
- Exit Options: IPO or strategic acquisition at $1B+ valuation
This roadmap positions Expert Fabric to capture the growing AI-human collaboration market while building sustainable competitive advantages through network effects, technical innovation, and global scale.