AI Agent Development and AI Integration Services

AI integration is the other half of the work: connecting a model to your documents, databases and tools safely, so it only sees what the person asking is allowed to see, and so every answer can be traced to its source.

We build both. Our team has built AI agents and integrations for large enterprise teams, under their security reviews and data-loss rules, as well as small assistants for local businesses.

• A small business that answers the same twenty questions every week and would like a website assistant that answers them from its own information.
• A growing company whose staff hunt through shared drives, old emails and wikis for answers that already exist somewhere.
• A support or operations team that wants drafts, summaries and lookups done before a person picks up the case.
• An enterprise IT or innovation team rolling out Copilot or another AI platform that needs agents built properly, with governance and evaluation.

Assistants that answer from your documents

Retrieval-augmented generation, usually shortened to RAG, means the assistant searches your own documents first and answers from what it finds, with the source shown. We set up the search, decide how documents are split and indexed, and test whether the right source comes back for real questions.

Copilot Studio agents for Microsoft 365

For companies on Microsoft 365, agents built in Copilot Studio can live in Teams and respect the permissions your staff already have. We build the topics, the actions, the connectors and the approval flows in Power Automate, and we work within the environment and data policies your IT team sets.

MCP servers and tool connections

The Model Context Protocol (MCP) is an open standard for giving AI assistants safe, well-defined access to a system. We build MCP servers that let assistants in tools like Claude, VS Code or Copilot Studio search your knowledge or call your systems, with sign-in, logging and a clear list of what each tool may do.

AI added to the software you already have

A search box that understands questions, a summary at the top of a long record, a classifier that sorts incoming requests, a draft reply someone approves. We add these to existing web apps and workflows through the model providers' APIs. See custom software development for the app side.

Website assistants for small businesses

A chat assistant on your site that answers common questions from your own pages and policies, takes contact details after hours and passes everything else to a person. It never pretends to be a person.

We build on the platform your company already trusts:

• Microsoft: Copilot Studio, Power Platform, Azure OpenAI, Azure AI Search, Azure Functions and Entra ID sign-in
• Google Cloud: Vertex AI, Cloud Run and Google Workspace data
• AWS: Amazon Bedrock, Lambda and S3
• Model APIs: Claude and GPT models through their business APIs, when you want to stay platform-neutral

The model is rarely the hard part. Most of the work is in the data, the permissions, the testing and the hand-off to a person, and those decisions carry over whichever platform you choose.

1. Discovery. We start from the job, not the technology: who asks what, how often, what a good answer looks like and what must never happen. We collect real questions and their right answers.
2. A written scope and a fixed price. The statement of work (SOW) says what the agent will do, what it will not do, which systems it touches and how we will measure it, before any build.
3. Build a first version on real data. A narrow first version, tested against your real questions from the first week.
4. Evaluate and tighten. We measure how often the right source comes back and the answer is right, fix the gaps, and repeat. You see the numbers.
5. Launch with guardrails. A limited roll-out first, logging of unanswered questions, a way for users to flag a bad answer, and a person approving any action that matters.
6. Keep it honest. Documents change and questions drift, so we re-run the test set on a schedule and update the agent when results slip.

• The agent only sees what the person asking is allowed to see.
• Every answer shows its source, so people can check it.
• Actions that change data or speak for you need a person's approval unless you set a specific, low-risk exception.
• Unanswered and flagged questions are logged for a person to review.
• Customer and company data stays in accounts you control, on business plans that do not train on it.
• The agent says it is an AI assistant. It never pretends to be a person.

• We will not promise that AI will make your business faster or cheaper. We will measure what it does and tell you.
• We will not build an agent that sends money, signs agreements or gives legal, medical or financial advice on its own.
• We will not connect an agent to data without your IT or data owner agreeing to it in writing.
• We will not launch without a test set of real questions and a result you have seen.

We describe our work without naming clients until they agree, and we keep the details of other companies' systems to ourselves. On the first call we can walk you through the kinds of agents we have built, the platforms they ran on and how we tested them.

Our own open-source MCP server for Power Platform governance is public. It combines keyword and semantic search, and on a labeled set of 35 test questions it shows the right page first 89% of the time, ahead of either search method alone. It is the same evaluation habit we bring to client builds.

We have not yet launched a customer-facing chatbot or phone assistant for a client, so we do not show one.

AI agent projects vary more than most software, because the cost sits in the data, the systems and the testing. We start with a discovery call, then send a statement of work (SOW) with the scope, the timeline and a fixed price before we build. Small website assistants are much smaller projects than enterprise agents, and we say so on the first call.

KORB is a studio in Logan, Utah. We work with businesses in Cache Valley and across Utah in person, and with companies of every size anywhere in the US over video.

Send us ten questions your staff or customers ask most, and where the answers live today. We will tell you whether an agent would help, what the first version would do and how we would measure it.