Schema Driven AI transforms how organizations build, deploy, and scale intelligent operations — from a single schema definition to autonomous enterprise applications.
Most organizations experiment with AI. Few operationalize it. The gap between a proof of concept and a production system is where ambition goes to die.
Critical decisions, processes, and institutional knowledge live in meeting recordings, scattered documents, chat threads, and people's heads. AI can't use what it can't access.
When AI agents act on behalf of your organization, you need to know why. Without decision lineage, you're flying blind — unable to audit, improve, or trust autonomous operations.
Adding AI to existing applications creates brittle integrations. Every new capability requires custom engineering. The cost compounds while the value plateaus.
Enterprise AI requires governance, role-based access, audit trails, multi-tenant isolation, and compliance. Building all of this from scratch for every project is unsustainable.
Purpose-built from token I/O to generated UI. Every layer is designed to work in concert — creating compound intelligence that deepens with every interaction.
Each capability is powered by the coordinated effort of multiple layers — not bolted on, but woven in.
Define a domain schema. Receive a complete enterprise application — database, APIs, UI, role-based access — generated and ready to deploy.
Layer 9 — CompilerIngest meetings, documents, chats, and calls into a unified knowledge layer with decision lineage that traces every insight to its origin.
Layer 11 — KnowledgeConfigure AI agents as virtual employees with strategic goals, KPIs, communication preferences, and maturity levels that evolve with confidence.
Layer 10 — AgentsKnowledge doesn't just sit in storage — it accumulates, cross-references, and compounds. Every interaction makes the next one smarter.
Layers 7-8 — OrchestrationAutomatically identify where institutional knowledge is missing, undocumented, or not AI-digestible — then guide teams to fill those gaps.
Layer 11 — KnowledgeEvery AI action traces back to a strategic goal. Evaluation frameworks, reward models, and rollout gates ensure trust at enterprise scale.
Layer 6 — GovernanceA systematic progression — not an experiment. Each phase builds on the last, creating deeper intelligence at every step.
Model your business domains, entities, and relationships. The schema becomes the single source of truth for everything that follows.
The compiler generates your full-stack application — databases, APIs, UI, permissions, and routing — all from the schema definition.
Ingest organizational knowledge. Documents, recordings, conversations, and processes flow into the intelligence stack where they're indexed and connected.
Deploy virtual employees that start in copilot mode, build confidence through verified actions, and progress toward autonomous operations.
Domain-specific configurations, virtual employee templates, and process libraries — all running on the same underlying stack.
Clinical workflows, compliance documentation, patient communication protocols, and HIPAA-aligned governance out of the box.
Regulatory reporting, risk assessment models, audit trail compliance, and automated financial analysis with decision lineage.
Supply chain optimization, quality control SOPs, equipment maintenance protocols, and production intelligence.
Route optimization, inventory management, carrier communication, and real-time operational decision support.
Customer experience workflows, brand consistency management, inventory intelligence, and omnichannel coordination.
Project methodology codification, client engagement automation, resource allocation intelligence, and knowledge transfer.
Custom integrations for every feature. Brittle, expensive, slow to adapt.
Pilots that never graduate. No systematic path from prototype to production.
Information scattered across tools with no lineage, no connections, no compounding.
Generic chatbots with no understanding of your business context or strategic goals.
Define once, generate everything. Applications that are born AI-native.
A proven path from observation to copilot to autonomous operations with confidence scoring.
Every decision traceable. Every insight connected. Intelligence that compounds over time.
AI agents with KPIs, goals, and communication preferences — configured for your business.
Join the organizations building systematic AI operations — not experiments. Early access is open for qualified enterprises.