AI Applications & Managed Services
LLM assistants, RAG pipelines, classification models — operated as a service.
AiCX's AI Applications and Managed Services practice operates production AI systems on behalf of enterprise clients — LLM-based assistants, RAG pipelines, classification models, and the orchestration layers that turn raw model capability into business outcomes. We design, deploy, and run these systems as a managed service, so clients get the value of generative AI without staffing the rare skill set required to operate it well.
Our team includes ML engineers, prompt engineers, RAG architects, MLOps practitioners, and the application engineers who wire AI into existing business systems. We operate across the major model providers (OpenAI, Anthropic, Google, Mistral, Meta) and run open-source models in private environments where data residency or cost demand it.
Managed services include the full stack: prompt engineering, evaluation harnesses, RAG pipeline operations, observability, cost management, hallucination monitoring, and the human-in-the-loop workflows that catch what models get wrong. We treat AI as a production system — not a science project.
The difference is in how we run the program — not the deck.
Plenty of vendors can quote you a seat. Few can deliver an outcome. Here's what changes when AiCX runs your ai applications & managed services program.
Production AI, not pilots
We operate AI as a production system — eval harnesses, observability, cost control, and rollback discipline.
Model-agnostic
OpenAI, Anthropic, Google, Mistral, Meta, plus open-source models in private environments.
RAG done right
Embedding strategy, chunking, retrieval evaluation, and grounding monitored continuously — not assumed to work.
Hallucination defense
Real-time grounding checks, citation enforcement, and human-in-loop for sensitive workloads.
Cost engineering
Token economics, caching, model routing, and prompt compression baked into operations.
Security and compliance
Private deployments, data residency, PII handling, and audit trails for regulated workloads.
Everything you need on day one — built in.
A ai applications & managed services program from AiCX ships with the operational scaffolding most clients spend quarters trying to assemble in-house.
- LLM-based assistant design and operation
- RAG pipeline architecture and operations
- Embedding model selection and tuning
- Vector database operations (Pinecone, Weaviate, pgvector, Chroma, Qdrant)
- Prompt engineering and template management
- Eval harness design and continuous evaluation
- Hallucination and grounding monitoring
- Multi-model orchestration and routing
- Open-source model deployment (private/on-prem)
- Token cost engineering and optimization
- PII detection and redaction
- Human-in-the-loop workflow integration
How teams put ai applications & managed services to work.
Wealth advisor research assistant
RAG-grounded LLM assistant on internal research; reduced advisor research time 38% with full citation requirement and compliance review.
Provider documentation assistant
HIPAA-compliant LLM assistant for clinical documentation; cut documentation time 28% with full audit trail.
Contract analysis pipeline
RAG + classification pipeline reviewing 80K contracts/year with human review on flagged clauses; cut review cost 47%.
Common questions about AI Applications & Managed Services.
Don't see your question? Talk to our solutioning team — we'll walk you through pricing, footprint, and ramp options for your specific program.
Related services
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BOT Development
Conversational and task-automation bots with ongoing tuning.
AI Virtual Agents
Voice and chat agents with seamless human escalation.
Ready to deploy AI Applications & Managed Services?
Schedule a 30-minute working session with our solutioning team — bring your KPIs, leave with a delivery plan.