Devana Control™
Governance, SLA & Regulatory-Grade Monitoring
for Critical AI Systems
Devana is an instrumented, governed, and contractually bound system designed to operate in critical and regulated environments.
Contractual SLA
Up to 24/7 coverage, with response in under 30 minutes
Continuous Update Guarantee
Structured anti-obsolescence framework over time
EU Compliance by Design
Auditable architecture compliant with AI Act, DORA and GDPR
Control spans from system level down to individual messages, with complete traceability at every layer.
GOVERNANCE
System Governance & SLA Framework
Supervision for mission-critical systems
Devana operates under tiered SLA commitments, scaling to full 24/7 coverage for mission-critical deployments.
Diamond tier includes
This framework enables
SLA Commitments
SLA is not a commercial argument. It is a structural governance mechanism.
DURABILITY
Continuous Update Guarantee
The foundation of quality and system longevity
The quality of an AI system is not defined by its initial state. It is defined by its capacity to remain compliant, secure, and compatible over time.
The Guarantee ensures:
This approach delivers:
Prevents obsolescence
Systems stay current with evolving technologies and standards
Reduces attack surface
Continuous patching and security hardening
Maintains regulatory compliance
Ongoing alignment with evolving regulatory requirements
Stabilizes the software lifecycle
Predictable update cadence with structured release management
The Continuous Update Guarantee is not an add-on. It is the foundation of system durability.
COMPLIANCE
EU Compliance by Design
Strict regulatory discipline
Devana is architected to operate in environments subject to:
Complete Traceability
Formalized Incident Governance
Continuous AI Behavior Supervision
Clear Shared Responsibility
Devana is not simply EU regulation compatible. It is architected to demonstrate compliance.
MONITORING
Multi-Layer Monitoring Architecture
From macro to micro
Infrastructure Control
- Docker image versioning
- Automated dependency analysis
- Vulnerability supervision
- Secured CI/CD pipelines
Objective:Technical stability and lasting security
Platform & Load Monitoring
- Message volume
- Token / model distribution
- Average latency
- Load peaks
- Error rates
Objective:Capacity control and performance
Agent-Level Behavioral Control
- Quality score
- Reliability scoring
- Token efficiency
- Tool usage
- Multi-agent comparison
Objective:Behavioral reliability
Message-Level Traceability
- Model used
- Response time
- Tokens consumed
- Risk assessment grade
- Conversation drill-down
Objective:Fine-grained auditability and operational justification
Predictive Load Simulation
- Load simulation on real configuration
- TPS / latency / stability observation
- Contention point identification
Objective:Anticipate risk before production
Full Traceability Interface: complete visibility into every AI decision. Every LLM call, every retrieved source, every tool invocation: visible, measurable, and auditable.
Explore the X·AIS traceability methodologyPRODUCTION TOOLING
Intelligent Orchestration & Production Control
Devana provides proprietary orchestration tooling designed to control how AI systems behave under load and ensure agent reliability over time, within customer-managed infrastructure.
Rather than promising performance, Devana equips organizations with instrumentation and validation mechanisms required to operate AI systems responsibly and auditably at scale.
AI Monkey™
Load testing Devana + your AI models on your infrastructure
AI Monkey stress-tests Devana combined with your AI models, running on your own infrastructure. It reproduces real operational conditions: your knowledge bases, your active microservices, your chosen LLM, your hardware (GPU type, server configuration), under peak and cumulative user load.
The result is a precise map of capacity limits, growth barriers, and projected costs before anything reaches production.
Verifies infrastructure capacity under realistic load with precise visibility on limits and improvement opportunities
Challenger
Agent reliability, quality assurance, and behavioral stability
Challenger systematically evaluates your AI agents before and after deployment. It runs structured question sets against multiple agents simultaneously, measures response quality via RAG scoring, and tracks token efficiency.
It identifies performance gaps, behavioral drift, and optimization opportunities.
Simultaneous evaluation of multiple agents with RAG accuracy, response quality, and consistency metrics
Observed performance depends on infrastructure configuration, agent setup, and deployment context
Ready to build the framework
for your AI governance?
Performance depends on infrastructure. Control depends on the framework. And that framework is precisely what we deliver.