Fuzzy Logic Engine
Non-rigid reasoning that handles uncertainty, partial matches, and degrees of truth. Real-world data is messy—your reasoning engine should handle that gracefully.
Neuro-Symbolic AI Platform
The ReasoningBackbone
The reasoning layer that makes enterprise AI trustworthy, auditable, and cost-effective.
đź’°Slash LLM Costs
🛡️Trustworthy AI
🎯Fix Hallucinations
đź“‹Full Auditability
🧠True Logic Reasoning
⏱️Temporal Reasoning
🌊Fuzzy Logic
✨Smart Context Optimization
Early Access
Get early access to
ReasoningLayer
Join the waitlist to be among the first to build with enterprise-grade neuro-symbolic AI.
Real-World Applications
Power your AI
with true intelligence
From recommendation engines to intelligent agents, ReasoningLayer transforms how you build AI systems with your own data and domain knowledge.
Transform Your Data Into
Actionable Insights
Your enterprise data holds untapped potential. ReasoningLayer's neuro-symbolic engine unifies your entire data landscape—surfacing insights that pure ML models miss, with full explainability and audit trails your stakeholders can trust.
10x
Faster insight discovery
100%
Explainable decisions
Zero
Black box reasoning
Cut LLM spending with intelligent context selection and precise tool routing
Smart Context Engineering
Domain-aware prompt optimization
Stop stuffing prompts blindly. Your domain knowledge knows what's relevant. Automatically inject the right context—entity relationships, business rules, constraints—based on the user's intent. No more token waste, no more missed context.
- Intent-driven context selection
- Automatic entity & relationship injection
- Token-efficient prompt construction
- Dynamic context based on conversation state
Smart Tool Selection
Ontology-driven tool selection
Stop guessing which tool to call. Your ontology—types, relations, constraints, hierarchies—knows exactly which tools are relevant for each task. Not embeddings, not keyword matching: real structural understanding. Works with MCP, OpenAI function calling, or any tool protocol.
- Full ontology matching: types, relations, constraints
- Works with MCP, function calling, any protocol
- Auto-generate tool schemas from your domain model
- Precise routing = fewer wasted API calls
LLM-Free Reasoning
Zero tokens for pure logic
Most queries don't need an LLM at all. Constraint solving, rule evaluation, type checking, consistency validation—all run locally with pure symbolic inference. Only use LLM tokens when you actually need language understanding.
- Pure symbolic inference = zero API costs
- Runs offline on any device
- Deterministic results, infinitely cacheable
- LLM only for ingestion & natural language
Recommendation Engine
Based on YOUR data
Build powerful recommendation systems that understand your domain semantics. Unlike black-box ML models, every recommendation is explainable and traceable back to your ontology and business rules.
- Semantic matching beyond simple vectors
- Explainable recommendations with proof traces
- Real-time personalization with constraint satisfaction
- Combine user preferences with business rules
Powered by Data-to-Knowledge
Your knowledge generates everything
Define your domain once. Agents, dashboards, and applications emerge automatically from your semantic model.
Auto Agent Generation
Agents born from your knowledge
Your domain knowledge defines your business. Why manually code agents? ReasoningLayer auto-generates specialized agents from your ontology—each agent inherits domain expertise, constraints, and reasoning capabilities. Update the knowledge, agents evolve automatically.
- Agents generated from ontology structure
- Inherited domain constraints & rules
- Auto-updated when knowledge evolves
- No manual prompt engineering needed
Auto Reports & Dashboards
Analytics that understand your data
Traditional BI requires manual schema mapping. ReasoningLayer understands your semantic model—automatically generates meaningful reports, KPIs, and dashboards. Ask questions in natural language, get visualizations grounded in your domain knowledge.
- Self-generating KPIs from semantic model
- Natural language to visualization
- Drill-down paths follow ontology relations
- Anomaly detection based on domain rules
Concept-Driven Applications
Apps that evolve with your domain
Build applications around concepts, not tables. Your UI, validations, and workflows derive from your knowledge structure. Add a new concept? The app adapts. Change a relationship? Forms update automatically. Your domain model IS your application logic.
- UI components generated from ontology
- Validation rules from domain constraints
- Navigation follows concept relationships
- Schema changes propagate instantly
Applications
Built for
enterprise AI
Healthcare
Clinical Decision Support
Explainable diagnosis with full audit trails for medical compliance.
Finance
Fraud Detection
Real-time analysis with auditable rule chains and pattern matching.
Legal
Contract Analysis
Automated compliance checking against regulatory frameworks.
Security
Access Control
Dynamic RBAC with policy inheritance and conflict resolution.
Manufacturing
Quality Assurance
Constraint-based defect detection with traceable decisions.
Research
Knowledge Graphs
Semantic reasoning over complex ontologies with LLM integration.
Why ReasoningLayer
Beyond traditional
neuro-symbolic systems
Most symbolic AI systems are rigid, hard to scale, and lack enterprise-grade security. ReasoningLayer changes everything.
Temporal Reasoning
Native support for time-aware inference. Reason about events, durations, sequences, and causality. Track how facts evolve and expire over time.
Formal Proof Trees
Every inference produces a verifiable proof tree. Mathematical guarantees for correctness. Export proofs for regulatory compliance and audit trails.
Truly Scalable
Unlike classical Semantic Web stacks, ReasoningLayer scales horizontally. On-premise or SaaS deployment. Handle millions of rules without performance degradation.
Auto-Modeling Ontologies
LLM-assisted ontology generation from your data with human curation when needed. No PhD in knowledge engineering required—we help you build your domain model.
Algorithm Resolution
Solve complex constraint problems by declaring rules, not writing algorithms. Scheduling, planning, optimization—let the engine find solutions automatically.
Residuation Engine
Automatic suspension when data is incomplete. Reasoning resumes seamlessly as new information arrives. No manual orchestration needed.
Flexible Deployment
Your infrastructure, your rules. Deploy on-premise for full data sovereignty, or use our managed SaaS. Air-gapped installations available for sensitive environments.
Neural-Symbolic Bridge
Best of both worlds: LLMs handle natural language and ambiguity, symbolic engine ensures correctness and explainability. Each does what it does best.
Enterprise Security
Security-first
by design
Multi-layer isolation, fine-grained access control, and compliance-ready infrastructure for the most demanding enterprise environments.
Multi-Layer Segmentation
Complete data isolation at every level
Tenant
Organization-level isolation
Namespace
Project/team boundaries
Collection
Fine-grained data groups
Each layer provides cryptographic isolation. Cross-tenant data access is architecturally impossible.
Advanced RBAC
Granular permissions at every scope
Role Inheritance
Hierarchical permissions from tenant to collection
Custom Policies
Define rules based on attributes, time, location
Audit Logging
Complete trail of all access and modifications
API Key Scoping
Restrict keys to specific namespaces/collections
Compliance Ready
Compliant with infrastructure for regulated industries
HIPAA
GDPR
ISO 27001
SOC 2
SecNumCloud
HDS
AI Governance
Built for
AI regulation compliance
ReasoningLayer is designed from the ground up to help you meet current and future AI regulations worldwide. Full auditability, explainability, and human oversight built-in.
EU AI Act Ready
Full compliance with Europe's landmark AI regulation
Effective Aug 2025
Risk Classification
Automated risk-tier assessment for your AI systems
Technical Documentation
Auto-generated compliance docs with model specs and training data provenance
Human Oversight
Built-in human-in-the-loop controls and intervention mechanisms
Conformity Assessment
Pre-built templates for CE marking requirements
Global AI Regulations
Ready for worldwide compliance
NIST AI RMFUSA
Risk management framework alignment
ISO 42001International
AI management system certification ready
AI Basic ActSouth Korea
Trust and transparency requirements
GDPR AIEU
Data protection for AI systems
Compliance Capabilities
đź“‹
Full Audit Trails
Every decision logged with complete proof traces and reasoning paths
🔍
Explainable AI
100% transparent reasoning—no black-box decisions
👤
Human Oversight
Configurable intervention points and override controls
đź“Š
Bias Monitoring
Continuous fairness metrics and drift detection
🛡️
Data Governance
Training data provenance and quality documentation
⚡
Incident Reporting
Automated serious incident detection and reporting
Future-proof your AI
Don't wait for regulations to catch up. Build compliant AI systems from day one.
Learn more
Dive deeper into how ReasoningLayer works and explore industry use cases.
Enterprise Program
We help you
integrate & succeed
Every enterprise is unique. Our team works alongside yours to design, implement, and optimize ReasoningLayer for your specific use cases—from proof of concept to production at scale.
Architecture Design
Custom Use Case Development
Proof of Concept
Training & Enablement
Ready to add reasoning
to your AI?
Join teams building explainable, auditable AI systems.
contact@kortexya.com