AI Infrastructure for Engineering Leaders
Build AI systems that scale with context, maintain consistency, and deliver reliable decisions—without sacrificing engineering velocity.
The Challenge You're Facing
❌ Inconsistent AI Behavior
Your AI agents make different decisions in similar contexts, making them unreliable for production use. You spend more time debugging edge cases than building features.
❌ Context Doesn't Scale
Cramming everything into prompts hits token limits and degrades performance. Your team is stuck manually maintaining fragile prompt templates.
❌ Black Box Decision-Making
You can't explain why your AI made a decision, making it impossible to debug, audit, or improve. Stakeholders don't trust the system.
❌ No Learning Infrastructure
Every mistake gets repeated because your system has no way to learn and improve from production experience without full retraining.
Engineering-First AI Infrastructure
ZUNFT.AI provides the missing infrastructure layer that makes AI systems production-ready for engineering teams.
PRO-Protocol: Structured Reasoning
Replace fragile prompts with a formal reasoning protocol. Get consistent, explainable decisions every time.
- • Deterministic decision-making within bounded contexts
- • Full reasoning chain capture for debugging and auditing
- • Version-controlled reasoning frameworks
Intelligence Layer: Context at Scale
Move context out of prompts and into a dedicated infrastructure layer that scales with your system.
- • Hierarchical context management (purpose, knowledge, reality)
- • Dynamic context injection based on reasoning needs
- • No token limit constraints on contextual information
Cognitive Loop: Continuous Learning
Build systems that learn from production without retraining. Mistakes become learning opportunities.
- • Automatic outcome tracking and reflection
- • Framework refinement based on real-world performance
- • A/B testing for reasoning strategies
Observability & Control
Full visibility into AI decision-making with engineering-grade tooling for debugging and monitoring.
- • Reasoning chain visualization and debugging
- • Performance metrics and decision quality tracking
- • Runtime controls and guardrails
Built for Production Engineering
Ship Faster
Stop debugging prompts and edge cases. Our structured approach reduces iteration time by 10x.
Production Ready
Enterprise-grade observability, monitoring, and controls from day one. No black boxes.
Scales Linearly
Context management that grows with your system complexity, not against it.
Testable
Deterministic reasoning means reliable unit tests and integration tests for AI behavior.
Maintainable
Version-controlled reasoning frameworks that your team can collaborate on like code.
Self-Improving
Systems that learn from production feedback and get better without manual intervention.
Built for Production at Scale
🏢Deployed Across Industries
Financial Services
Risk assessment & regulatory compliance
B2B SaaS
Product intelligence & validation systems
Healthcare
Clinical decision support systems
Enterprise
KPI governance & strategic planning
⚙️Enterprise-Grade Infrastructure
95% Test Coverage
Comprehensive automated testing across all domains
Multi-Tenant Architecture
Supporting concurrent enterprise deployments
Enterprise Security
VPC Service Controls, Binary Authorization, SOC 2 ready
Observable Intelligence
Real-time friction detection and performance monitoring
Pre-Built Intelligence Domains
ZUNFT.AI includes production-ready intelligence domains you can deploy immediately, plus custom domains tailored to your business context.
KPI Governance Intelligence
zunftAI Domain
Prevent catastrophic metric failures like Facebook's engagement optimization or 2008's VaR models. Analyzes AI-generated KPIs for philosophical alignment before deployment.
Business Validation Intelligence
Real Progress Framework
Evidence-based startup validation using Real Progress Framework. Tracks killer assumptions, orchestrates validation experiments, assesses evidence quality.
Financial Planning Intelligence
Model Generation & Validation
Automated financial model generation with constraint validation. Scenario analysis, revenue/cost projections, sensitivity testing with full transparency.
Your Custom Domain
Tailored Intelligence
We build domain-specific intelligence tailored to your business context. Your reasoning frameworks, your business logic, your competitive advantage.
Engineering Teams Using ZUNFT.AI
LLM-as-a-Judge Systems
Build consistent evaluation and quality control systems that scale across your entire platform.
Result: 95%+ decision consistency, full audit trails, continuous improvement loops
Autonomous Agents
Deploy agents that understand context deeply and make reliable decisions without constant human oversight.
Result: 70% reduction in human intervention, transparent reasoning chains
Complex Decision Systems
Handle multi-stakeholder, multi-criteria decisions with explainable AI that stakeholders trust.
Result: Complete decision traceability, stakeholder alignment, regulatory compliance
AI-Powered Workflows
Orchestrate complex workflows where AI needs to understand business context and make judgment calls.
Result: Reliable automation of complex processes, exception handling that scales
How ZUNFT.AI Works With Your Team
Our proven 8-week process takes you from scoping to production deployment with full observability.
Scoping & Architecture Design
- → We analyze your AI use case (LLM-as-Judge, autonomous agents, decision systems)
- → Design your context structure and reasoning frameworks
- → Define success metrics and observability requirements
Integration & Deployment
- → Connect to your LLM providers (OpenAI, Anthropic, Azure)
- → Deploy PRO-Protocol reasoning layer to your infrastructure
- → Set up Intelligence Layer for context management
- → Configure observability dashboards and monitoring
Production Rollout
- → A/B test reasoning strategies against your baselines
- → Activate Cognitive Loop for continuous learning
- → Train your team on framework management
- → Monitor and optimize decision quality
Self-Improving System
- → Your system learns from production outcomes automatically
- → Frameworks refine based on real-world performance
- → Your team iterates on reasoning strategies
- → Full transparency into all AI decisions and improvements
Ready to Deploy Production-Grade AI Intelligence?
Our proven engagement process takes you from scoping to production deployment in 8 weeks.
30-Minute Scoping Call
We'll analyze your AI use case and recommend the right intelligence architecture for your needs.
Technical Architecture Review
Our team designs your reasoning frameworks and integration plan (2-3 days).
Proof of Value (Week 1-4)
Deploy to your dev environment, test against your data, validate improvements before full commitment.
Production Rollout (Week 5-8)
Full deployment with observability, monitoring, and team training. Your system is production-ready.