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AI Agents & LLM Integration (.NET/Node)

$45/hr Starting at $500

Turn AI from a demo into a working part of your product or operations. I design and build AI agents and LLM features that live inside your existing .NET or Node.js systems, with the authentication, logging and error handling a business application needs.


WHAT YOU GET

• An AI assistant or agent using the Claude or OpenAI APIs, with tool calling into your own APIs and databases.

• Retrieval-augmented generation (RAG) over your documents, tickets, or database records, with citations, using PostgreSQL and pgvector or Azure AI Search.

• Connection to your systems through tool calling, or through my MCP Servers service when the assistant needs to act, not just answer.

• Guardrails: permission checks, human approval steps, cost limits, and full audit logs of every model call.

• Deployment to Azure, AWS or Kubernetes with Docker, plus CI/CD.


TYPICAL PROJECTS

• "Ask our data" assistant for internal teams over policies, contracts or product documentation.

• Agent that reads a request, gathers context from three systems, drafts the response, and waits for a human to approve.

• Adding an AI copilot to an existing ASP.NET Core or React application.


WHY ME

15 years building enterprise .NET systems means I know where AI fits and where it does not. I have built agent pipelines and MCP integrations for a multi-service .NET platform and I am comfortable with the unglamorous parts: security, cost control, testing, and observability.


HOW IT STARTS

A 30-minute call, then a written plan with milestones. Minimum engagement $500. Fixed-price packages available for a defined scope.

About

$45/hr Ongoing

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Turn AI from a demo into a working part of your product or operations. I design and build AI agents and LLM features that live inside your existing .NET or Node.js systems, with the authentication, logging and error handling a business application needs.


WHAT YOU GET

• An AI assistant or agent using the Claude or OpenAI APIs, with tool calling into your own APIs and databases.

• Retrieval-augmented generation (RAG) over your documents, tickets, or database records, with citations, using PostgreSQL and pgvector or Azure AI Search.

• Connection to your systems through tool calling, or through my MCP Servers service when the assistant needs to act, not just answer.

• Guardrails: permission checks, human approval steps, cost limits, and full audit logs of every model call.

• Deployment to Azure, AWS or Kubernetes with Docker, plus CI/CD.


TYPICAL PROJECTS

• "Ask our data" assistant for internal teams over policies, contracts or product documentation.

• Agent that reads a request, gathers context from three systems, drafts the response, and waits for a human to approve.

• Adding an AI copilot to an existing ASP.NET Core or React application.


WHY ME

15 years building enterprise .NET systems means I know where AI fits and where it does not. I have built agent pipelines and MCP integrations for a multi-service .NET platform and I am comfortable with the unglamorous parts: security, cost control, testing, and observability.


HOW IT STARTS

A 30-minute call, then a written plan with milestones. Minimum engagement $500. Fixed-price packages available for a defined scope.

Skills & Expertise

.NETAI Agent DevelopmentAmazon Web ServicesAPI DevelopmentArtificial IntelligenceC#ChatbotsChatGPTCloud ComputingDocker SoftwareLLMMicrosoft AzureNode.jsOpenAI APIPostgreSQLRAGSystem Architecture

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