nostedt.

Marketing by Cameron Nostedt.
Winnipeg, Manitoba.

MAKE AI USEFUL
TO YOUR BUSINESS.

When staff spend hours finding information, copying data between tools or chasing incomplete requests, the cost shows up in slower service and less time for customers. I build AI systems that help your team find answers, process information and move work forward, with a clear business outcome agreed before development.

Find your AI opportunity

Start with the work that costs you time.

A useful AI project starts with a bottleneck: knowledge scattered across files, documents waiting to be entered, enquiries waiting for a reply or systems that do not share information. We identify the cost of that friction, choose an achievable first project and agree on what improvement would make it worthwhile.

The problem. The system. The value.

  • Your team cannot find the answer. RAG (retrieval-augmented generation) brings relevant material from your documents into an AI response. Embeddings represent meaning as vectors; vector search helps retrieve related information even when the wording differs. Useful for internal knowledge search, onboarding and support answers with source references.
  • Your tools leave people doing the handoffs. MCP (Model Context Protocol) connects AI applications to tools and data through a common interface. API (application programming interface) integrations and webhooks connect the underlying systems. Together, they can reduce copying between your CRM, inbox and project tools.
  • A task takes several steps across several systems. AI agents can use approved tools to retrieve information, prepare a response and route the next action. Workflow orchestration coordinates the steps, with permissions, logs and human approval for actions that need review.
  • Documents become a data-entry backlog. OCR (optical character recognition) and LLMs (large language models) can extract, classify and structure information from forms, PDFs and emails. Validation and exception handling help your team review uncertain results before records are updated.
  • Customers wait for routine answers. Chatbots and voice agents can answer approved questions, collect the details needed for a useful handoff and route enquiries. The value is a quicker response and a better-prepared conversation for your team.

Agree on the value. Then measure it.

Before building, we record a baseline: time spent per task, turnaround time, rework or unanswered enquiries. The pilot is assessed against those measures, alongside usage fees, maintenance and the time still needed for human review. That gives you a basis for deciding whether to expand, adjust or stop.

Experience behind the work

In my role at Hello Digital Marketing, I have built client-facing chatbots and voice agents, supported live systems and worked on document-processing workflows. That experience includes scoping, onboarding, launch and troubleshooting. These are examples of my agency-role experience, rather than projects commissioned directly through Nostedt.

From business problem to working system

  1. Map the opportunity: review the current process, data access, bottlenecks and cost. Choose the first use case and agree on success measures.
  2. Build a focused pilot: connect the required knowledge and tools, define permissions and test against representative tasks. Evaluate answer quality, retrieval, failure cases, latency and cost.
  3. Put it into use: document the workflow, train the team and agree on monitoring and support. Review real results before extending the system.

What affects the price?

The quote depends on the workflows, integrations, data preparation, access requirements and evaluation needed. Platform subscriptions, usage charges and ongoing support are identified separately. We can start with one workflow before considering a wider rollout.

You receive a written scope, timing and quote before work begins.

Get a project quote

Questions before we start

What should a business automate first?

Start with a repeated task that has clear rules, reliable information and an outcome you can check. Routine enquiries or collecting contact details are often easier to scope than a process that needs frequent human judgement.

Do I need a chatbot to use AI?

No. AI can work behind the scenes: searching internal knowledge, processing documents, drafting reports or coordinating tasks across your tools. The interface follows the job your team needs done.

Does RAG train a model on my documents?

RAG retrieves relevant source material for a response; it does not by itself retrain the model. We plan which sources the system can access, how they stay current and how responses are checked. Retrieval can improve grounding, but it does not guarantee a correct answer.

How do you handle access and approval?

We define which users, data and actions the system can access. Permissions, logging, data handling and human approval are part of the implementation scope. Connecting a tool through MCP or an API does not replace those controls.

Do you support AI systems after launch?

Support is agreed in the proposal. It can include troubleshooting, reviewing unanswered questions and updating the system as your business information changes.

Do I need to be in Winnipeg?

No. Workflow review, development, testing and handover can take place remotely.

LET’S GET
TO WORK.

Tell me where information gets stuck or your team loses time. We’ll work out whether AI can make a useful difference.

Talk to Cameron