Generative AI Applications
AI-enabled application experiences tied to specific business workflows and user outcomes.
← All services
Practical AI solutions
Put AI inside real workflows—not beside them.
Design assistants, retrieval experiences, intelligent automation, and AI-enabled applications around trusted data, controlled actions, evaluation, and human escalation.
Enterprise RAG and knowledge retrievalAI assistants and copilotsIntelligent workflow automationAI governance and evaluation
User / Workflow→AI Experience→Retrieval + Tools→Enterprise Systems
AI in context
Ground the model, control the actions, and measure the workflow.
AI creates durable value when it is grounded in approved information and connected to the workflow it is meant to improve. Arina focuses on production patterns: retrieval, enterprise knowledge, tool use, workflow orchestration, permissions, evaluation, observability, and controlled escalation.
AI capabilities
From knowledge retrieval to assistants, agents, and automation.
RAG & Knowledge Retrieval
Ground models in documents, knowledge bases, structured data, and enterprise content.
AI Assistants
Customer, employee, operations, and domain-specific assistants with escalation paths.
Workflow Automation
Classify, summarize, extract, route, draft, and trigger downstream actions.
Agents & Tool Use
Controlled multi-step AI workflows that invoke APIs and approved business actions.
Governance & Evaluation
Access, grounding, quality evaluation, monitoring, data handling, and human oversight.
Production path
Move from use case to governed production AI.
Choose the use case
Start with the user, workflow, pain point, data, expected outcome, and role of AI.
Design the AI system
Choose model, retrieval, data access, tool use, security, evaluation, and escalation.
Validate
Test quality, latency, cost, failure modes, security, and user experience before scaling.
Operationalize
Integrate into production with monitoring, feedback, versioning, controls, and continuous evaluation.
Grounded knowledge
Approved sources, retrieval, metadata, permissions, and traceable business context.
Controlled actions
Authentication, authorization, tool permissions, escalation, and safe failure modes.
Evaluated in production
Quality, latency, cost, user feedback, and workflow outcomes should remain observable.
Ways to engage
Start focused and expand as the initiative becomes clearer.
AI discovery workshopRAG architectureAI assistant deliveryAutomation implementationProduction AI governance
Start a conversation
Contact Arina Have an initiative that needs architecture, engineering, AI, operations, or specialist talent?
Share the current environment, problem, constraints, and desired outcome. We can help shape the right service approach.