AI Chatbot Development and Business AI

In short Chatbots trained on your own documentation, products and policies. They answer customers accurately, in your tone, hand off to a human when they should, and stay awake at 3 a.m. when your competitors don't. The same discipline sits behind AI marketing that actually converts: know the data, keep a person in the loop.

How we workFirst we count how many questions actually come in each day, since that decides whether a bot is even worth building. Then we gather your materials, set clear boundaries for what it will and won't answer, and decide exactly when it hands off to a person. Before launch, we test it against real questions pulled from your support inbox.

What you getA working chatbot live on your website, in your store, or inside the chat tool you already use, connected to your data so it can answer a question about a specific order. You also get a log of every conversation showing the source behind each answer, plus a simple way to correct the material when it gets something wrong.

In short Beyond chat: agents built with AI that actually do things. Process an order, draft a reply, update the CRM, chase an unpaid invoice. We keep the scope narrow, watch them closely, and only widen it once they've earned the trust.

How we workWe start with one narrowly scoped task, measure the time it actually saves, and only add another once that's proven. Connections run through the interfaces your systems already have, and anything sensitive waits for a person to confirm it. Before we build an agent at all, we check whether plain automation, no model needed, would do the job just as well and cost less to run and fix.

What you getAn agent that handles one specific task on its own, processing an order, drafting a reply for approval, updating your CRM or chasing an unpaid invoice. You also get a log of every step and the time it measurably saved, giving you a solid case for expanding what it does.

In short Search over your documentation, catalog or internal knowledge base that understands the question instead of matching words. For a shop it means search that still works with a typo, or when someone describes a feature instead of naming the product. For a company it means fewer repeat questions reaching support.

How we workWe process your sources, be it docs, a catalog or an internal knowledge base, so every answer links back to where it came from. We set permissions for what stays out of search and who can see what. Then we test the quality against a list of real questions your users actually ask.

What you getSearch where people type their question in their own words and see exactly which document the answer came from, working even with typos or a feature they describe instead of name. You also get a report on what people actually search for and where the answer is missing: the cheapest list of documentation gaps you'll ever get.

In short Invoices, contracts, forms: read, extracted, checked and filed with AI instead of by an intern with a sore wrist. A person reviews anything where the stakes are high; everything else runs on its own.

How we workWe work out the payback upfront, based on how many documents you handle each month. Then we train the system on your real documents, including scans, phone photos and PDFs with no text layer, and set a confidence threshold above which a document clears itself. Everything below that line goes to a person for review.

What you getA process that pulls the data out of your documents, checks it against what's already in your system, and routes any mismatch to a person. You also get a review queue, a log of every document, and a threshold you can adjust for what clears on its own.

In short An in-house assistant that has genuinely read your wiki, contracts and procedures, and answers staff questions privately and securely. New hires ramp up faster, and "just ask Karel, he knows" stops being your entire knowledge base.

How we workWe start by gathering your internal docs, policies and procedures, and sorting out what's still current from what died years ago. An assistant trained on stale material is worse than no assistant at all. We set who can read what by role, and connect it to the tools your team already uses. And we're upfront about its limits, including where the final call always stays with a person.

What you getAn assistant available right where your team already works, answering from your own internal material and respecting who's allowed to see what. You also get a report of the questions it couldn't answer, a ready-made list of what to add to the documentation.

In short Custom models for where off-the-shelf artificial intelligence runs out: demand forecasting, anomaly detection, recommendations, pricing. We only build one when the data justifies it, and we'll tell you plainly when it doesn't. The same models power AI marketing use cases too: pricing, recommendations, demand forecasts that hold up once they ship.

How we workWe start by checking the data, because its volume and quality decide the outcome more than the choice of method ever does. We build the simplest possible baseline, measure it, and only deploy a more complex model once it clearly beats that number. If the data turns out to be insufficient, we stop the project instead of spending more of your budget.

What you getA working model deployed for your specific task, with its accuracy monitored, since accuracy drifts over time. You also get a report on the data, the baseline the model was measured against, and exactly where its reliability limits sit.