# Services > AI strategy, solution architecture, agents, MCP servers, RAG, fine-tuning, MLOps, governance and senior AI engineers on demand. Source: https://aibyos.com/services Services # Everything between the idea and the _SLA_. Six ways to engage and nineteen hands-on capabilities, from agents and MCP servers to fine-tuning, voice and EU AI Act readiness. 01 · Services ## Pick one, or combine them. Click a service to see what it covers, related capabilities and example use cases. ◇ ### AI Strategy & Use-Case Discovery Find the use cases with real ROI, estimate cost and risk, and build a roadmap leadership can sign off on. - Opportunity mapping - Build vs. buy analysis - Business case & roadmap See use cases → △ ### AI Solution Architecture Reference architectures for LLM apps, agents and ML platforms that fit your cloud, data and security constraints. - Target architecture & ADRs - Model & vendor selection - Architecture reviews See use cases → ○ ### LLM, RAG & Agent Engineering Hands-on delivery of copilots, assistants, document intelligence and agentic workflows, with evaluation built in. - Retrieval & knowledge pipelines - Tool-using agents - Eval harnesses & guardrails See use cases → □ ### MLOps & LLMOps Platforms The plumbing that makes AI boring in the best way: deployment, monitoring, cost control and fast iteration. - CI/CD for models & prompts - Observability & tracing - Inference cost optimisation See use cases → ◎ ### AI Governance & Security Ship responsibly. Practical controls for privacy, safety and compliance, including EU AI Act readiness. - Risk classification - Prompt-injection & data-leak testing - Policies & model documentation See use cases → ☰ ### Senior AI Engineers on Demand Add experienced AI engineers and architects to your team, full-time or part-time, remote or hybrid, B2B-friendly. - AI / ML engineers - Data & platform engineers - Fractional AI architect See use cases → 02 · Capabilities ## The full modern AI stack, _hands-on_. Pick an area to see typical use cases, what we deliver and the tools we use. [◈AI Agents & Agentic Workflows](https://aibyos.com/services/agents)[⬡Agent Infrastructure & Runtime](https://aibyos.com/services/agent-infra)[⌘MCP Servers & Tool Integration](https://aibyos.com/services/mcp)[⇄AI Gateways & Model Routing](https://aibyos.com/services/gateway)[⌕RAG & Enterprise Search](https://aibyos.com/services/rag)[❖LLM Applications & Copilots](https://aibyos.com/services/llm-apps)[⚙Fine-tuning & Model Customization](https://aibyos.com/services/fine-tuning)[◐Image & Vision Models](https://aibyos.com/services/vision)[◉Voice & Speech AI](https://aibyos.com/services/voice)[▥Sovereign GPU Compute](https://aibyos.com/gpu)[∿Applied ML, LLM & Voice Research](https://aibyos.com/research)[✓Evaluation, Guardrails & AI Security](https://aibyos.com/services/evals)[▤MLOps, LLMOps & Inference](https://aibyos.com/services/llmops)[▦Data Foundations for AI](https://aibyos.com/services/data)[▣AI & Data Analytics Platforms](https://aibyos.com/services/platforms)[⛶Cloud & AI Landing Zones](https://aibyos.com/services/landing-zones)[⇆Cloud AI / LLM Migrations](https://aibyos.com/services/migrations)[➤AI Accelerators & Starter Kits](https://aibyos.com/services/accelerators)[⚖AI Governance & EU AI Act](https://aibyos.com/services/governance) ◈ ### AI Agents & Agentic Workflows Agents that plan, call tools and finish real work, safely. We design single- and multi-agent systems that take actions in your tools: triaging tickets, reconciling data, drafting and filing documents, running research. Every agent ships with clear permissions, human-in-the-loop checkpoints and an evaluation suite. #### Typical use cases ### Customer support agent **Challenge.** Tier-1 tickets pile up and agents copy-paste between CRM, billing and knowledge base. **What we build.** A tool-using agent that reads the ticket, looks up the account, drafts or executes the fix (refund, reset, update) within policy limits and escalates the rest with a summary. ### Back-office operations agent **Challenge.** Invoice matching, order exceptions and data corrections eat analyst hours. **What we build.** A workflow agent that reconciles records across ERP and email, proposes corrections and routes approvals, with a full audit log of every action. ### Research & analysis agent **Challenge.** Analysts spend days gathering sources before any real thinking starts. **What we build.** A multi-step research agent that searches internal and web sources, cites everything, and produces a structured brief your team can verify in minutes. #### What you get - Agent architecture & permission model - Tool / API integrations - Human-in-the-loop approval flows - Eval suite with task-success metrics #### Typical stack - Claude / GPT / Gemini - LangGraph - OpenAI Agents SDK - Claude Agent SDK - Pydantic AI - Temporal [Full details](https://aibyos.com/services/agents) [6 industry examples](https://aibyos.com/use-cases#cap-agents) Your need is not on this list, or spans several areas? 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