Agent Launch in 8

8 weeksFixed scope$75,000

From idea to launch in 8 weeks

A production-ready agent, integrated, deployed, and handed off in eight weeks.

Weeks 1–2 confirm the users, workflow, constraints, and success measures, then define the target architecture and lock the delivery scope.

Weeks 3–6 validate data and access, build the agent and guardrails, connect required systems, and run evaluation and tuning.

Weeks 7–8 complete UAT and release checks, finalize runbooks, deploy the agent, observe initial use, and enable its owners.

Hosted in MS Foundry Agent Service

Azure AI Agent

User

AI AgentCustom agent

MS Foundry ModelsApproved models

Azure AI SearchRAG

MS Foundry ToolboxTools & actions

MS Foundry ObservabilityTrace & evaluate

External ToolsAPIs & systems

Hosted in Databricks App.

User — A business user starts the workflow and reviews the agent response.
AI Agent (Custom agent) — A framework-based agent hosted in Databricks Apps coordinates model access, retrieval, Unity Catalog-governed data, and approved external tools through Unity Catalog connections or MCP Services.
Unity AI Gateway (Models & policies) — Unity AI Gateway controls access to approved foundation models, endpoints, and model policies.
AI Search (RAG) — Retrieves relevant governed knowledge to ground the agent response.
Unity Catalog (Governed data) — Provides governed tables, volumes, functions, permissions, discovery, and lineage for the agent workflow.
MLflow (Trace & evaluate) — Tracks traces, evaluation results, and production-quality signals for the agent.
External Tools (APIs & systems) — Connects approved APIs, operational systems, and business tools to the agent workflow.

Hosted in LangSmith Deployment.

User — A business user starts the workflow and reviews the agent response.
AI Agent (Custom agent) — A LangGraph or LangChain agent hosted in LangSmith Deployment coordinates models, knowledge, tools, state, and responses.
LangSmith LLM (Approved models) — Connects the agent to approved model APIs selected for the business workflow.
Vector store (RAG) — Supports retrieval-augmented generation with a provider selected during enablement, such as Azure AI Search, pgvector, or another approved service available in the target environment.
Tools & integrations (MCP, APIs & A2A) — Connects approved MCP servers, APIs, functions, and agent-to-agent integrations.
LangSmith (Trace & evaluate) — Captures traces, evaluates behavior, manages datasets, and monitors the deployed agent.
External Tools (APIs & systems) — Connects approved APIs, operational systems, and business tools to the agent workflow.