Build a production-ready AI operating system that serves as the central intelligence layer coordinating all AI agents, tools, data, and workflows across an entire company — making the organization itself function as an AI-native entity.
Core vision:
Create the "AI OS for companies" — the foundational platform that sits beneath all departmental AI tools and agents, providing shared infrastructure for agent orchestration, company-wide context, cross-functional workflow coordination, and governance. Just as an operating system abstracts hardware and provides shared services to applications, the AI OS abstracts data and provides shared services to AI agents across the organization.
The system must support the full organizational AI lifecycle:
1. Provide shared infrastructure all company AI agents run on
2. Maintain a unified, permissioned company knowledge graph
3. Coordinate multi-agent workflows across departmental boundaries
4. Enforce governance, compliance, and usage policies
5. Measure organizational AI performance and ROI
6. Continuously improve the company's AI capabilities over time
Core capabilities:
Company knowledge infrastructure:
- Unified ingestion pipeline for all company data sources (docs, email, Slack, CRM, ERP, code)
- Single permissioned knowledge graph accessible to all company agents
- Real-time synchronization as underlying data changes
- Entity resolution across systems (same customer in Salesforce and Zendesk unified)
- Semantic search and retrieval API used by all company agents
- Knowledge freshness tracking and staleness alerting
Agent registry and orchestration:
- Central registry of all AI agents deployed across the company
- Capability discovery: agents can find and invoke other specialized agents
- Workflow composition: build cross-departmental multi-agent workflows visually
- Agent scheduling: time-based, event-triggered, and on-demand execution
- Resource management: token budgets, API rate limits, cost allocation by department
- Inter-agent communication with message queuing and guaranteed delivery
Company context and memory:
- Organizational memory that persists across all agent sessions
- Company-wide goals, OKRs, and strategic priorities injected as context
- Customer history accessible to all customer-facing agents regardless of channel
- Decision history: why did the company decide X? Surfaces for all relevant queries
- Project and initiative tracking visible across departmental agent boundaries
- Contact and relationship graph available to all agents
Governance and compliance:
- Centralized AI policy management: what agents can/cannot do company-wide
- Data access controls: agents only access data their human user could access
- Output review queues for high-stakes AI-generated actions
- Complete audit log of every agent action, decision, and data access
- PII detection and redaction before AI processing
- AI usage reporting for regulatory compliance and board reporting
Cross-functional workflow engine:
- Visual workflow builder connecting agents from different departments
- Human approval steps built into any workflow
- Exception handling and escalation paths for failed agent actions
- SLA monitoring for workflow completion times
- Workflow version control and A/B testing
- Trigger system: business events kick off multi-department workflows
Organizational AI performance:
- Company-wide AI ROI dashboard: hours automated, decisions accelerated, errors prevented
- Department-level adoption and effectiveness metrics
- Agent performance leaderboard and worst-performer debugging
- Cost per automated workflow by type and department
- Employee AI capability index tracking skill development
- Benchmark company AI maturity vs. industry peers
Build a working demo covering:
1. Connect three data sources and see unified knowledge graph with entity resolution
2. Register two specialized agents and compose a cross-departmental workflow
3. Trigger the workflow from a business event and trace execution across agents
4. View the governance dashboard with agent actions and policy compliance
5. Show the company AI ROI dashboard with hours automated and cost savings
Builds a working MVP of a company-wide AI operating system. Connect multiple data sources and watch unified entity resolution, register specialized agents and compose a cross-department workflow, trigger it from a business event and trace execution, and view a governance dashboard with cost and compliance metrics.