An AI assistant for business, the way we build it, is an internal assistant with company knowledge: the team asks in natural language, and the answer comes from your offers, projects and procedures, not from the model's general knowledge. When something isn't in the documents, the assistant says it doesn't know, instead of guessing. The effect for the company: faster preliminary quotes, smoother onboarding and fewer questions pulling your busiest people away from their work. We build it on the knowledge you already have, around one process that eats the most time today.
What is an AI assistant for business and how does it differ from a website chatbot?
An AI assistant for business is a tool for your team, not for visitors on your website. A typical chatbot handles customers from a script, while an internal assistant reads the company's documents and answers the people who work there: about past projects, procedures, the way you quote. Two different products for two different jobs.
It makes sense where a company has a body of work: offers, completed projects, an established way of communicating. The longer you've been running, the more knowledge sits in documents and heads, and the more you can teach the assistant so it has something to answer from. How the mechanism works from the inside, we break down in the post on an AI assistant with company knowledge.
Why does a company need an assistant if the knowledge is already somewhere?
Because the knowledge is in the company, but usually in the head of the person who happens to be on leave. Your most experienced people are the bottleneck not because they work slowly, but because some things only they know. An assistant with company knowledge takes the repetitive questions off them: at our client, 80% of new employees' questions go to the assistant today, not the team.
There's one condition: the knowledge has to be written down. Software won't learn from chaos. If your documents are scattered, we put them in order together at the start of the rollout, because they're the fuel for the whole solution.
How does an AI assistant with a knowledge base work, and how do you know it won't make things up?
The assistant doesn't answer from the model's memory, but from your knowledge base. Before it forms an answer, it searches for matching passages in the company's documents and builds the answer only from them. When something isn't in the base, it says plainly that it doesn't know. With company knowledge, a made-up answer is worse than no answer, because someone will make a decision based on it.
Two things stay under your control. Style: we tune the answer language to the company, so it sounds like you, not like a generic model. Decisions: a final quote or a client commitment always passes through a person, the assistant prepares, you approve.
What results does an AI assistant with company knowledge deliver?
You see them fastest on preliminary quotes and onboarding. PEMA, a fencing-systems manufacturer running since 1998, rolled out with us an assistant based on its own body of work from hundreds of projects. Preliminary quotes are built from similar, previously completed projects, and new employees ask the assistant instead of pulling the team away.
“It helps us prepare preliminary quotes faster, basing them on similar, previously completed projects.”
Magdalena Peelen, Management Board Assistant, PEMA
The whole rollout, from the problem to the numbers, we describe in the PEMA assistant case study.
When does an AI assistant for a company NOT pay off?
In three situations we say it straight on the consultation. When the knowledge isn't written down anywhere and you have no room to put it in order. When there are a few repetitive questions a month, because then the cost has nothing to pay back from. And when the team's time drains elsewhere, for example retyping data between systems: then automating that process wins back more, and the assistant can wait. Where to start in that case, we describe in a guide to your first automation.
How much does an AI assistant for business cost, and what does the rollout look like?
Rolling out an assistant as one process begins at $1,000 (the Essential package, 30 days of support), and the first working version is ready in 7-14 days. The Professional package (up to three processes, integrations and a team workshop, 90 days of support) we quote individually after the audit. The return on the investment usually comes in 4-6 months. The package details are in our pricing.
- Free consultation (30 minutes): we check which questions and quotes eat the most time, and say straight if an assistant won't hold up at your company.
- Knowledge audit: we point out which documents go into the base and what's missing.
- First version in 7-14 days: the assistant answers your team's real questions.
- Tuning: we improve the style and the base's coverage based on real conversations.
- Support after launch: 30 days (Essential) or 90 days (Professional).
The first step costs nothing: on a free consultation we'll count how much time searching for information and preparing quotes eats today, and whether an assistant is the process with the shortest path to a return at your company.
Sources
- Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks - arXiv (Lewis et al., 2020)
- n8n documentation: workflows and integrations - n8n
