AI solutions
AI for the real workof your team.
WEB-AZ's AI solutions are agents, assistants and systems that take over repetitive tasks and prepare decisions. People stay in control where it matters.
Chatbot or AI agent?
Both hold conversations. The difference shows when something concrete has to be done in the systems you use.
Chatbot
AI agent
What it does
Answers questions based on a script or a text.
Follows a workflow: understands the request, looks up information, prepares or carries out steps.
Access to systems
Usually none, or very limited.
Uses only approved tools: CRM, calendar, databases, documents.
Actions
Provides information.
Creates a task, fills in a record, proposes a reply or a quote.
Control
Fixed rules.
Clear permissions, an action log and human approval for important steps.
When it fits
Simple, repetitive questions.
Multi-step processes where time is lost between apps.
How an AI agent works
- Input
- AI
- Action
- Human in the loop
- Result
- 01
Input
Receives the request
An email, a form, a message or an internal task.
- 02
AI
Understands the context
Identifies what is being asked and what information is missing.
- 03
Action
Uses tools
Searches the approved CRM, documents or databases.
- 04
Human in the loop
A person validates
Steps with impact are approved before they are carried out.
- 05
Result
Acts and reports
Completes the action and keeps a clear log.
Assistants built on your documents
RAG, explained for everyone
RAG (Retrieval-Augmented Generation) means the system first searches your configured sources and only then writes the answer. It increases relevance and lets you check the sources, but it does not eliminate every error.
More about RAG systems- Input
- Action
- AI
- Human in the loop
- 01
Input
The question
A colleague or a customer asks something specific.
- 02
Action
Search the sources
The relevant passages are found in the permitted documents.
- 03
AI
Answer with citations
The model writes the answer based on the passages found.
- 04
Human in the loop
Review and feedback
Uncertain answers are flagged and reviewed by the team.
01 / 04
AI agents
Assistants that follow the steps you set, use approved tools and see specific tasks through to the end.
- AI agent for salesPrepares quotes, follow-ups and replies from your CRM data, while the salesperson reviews them and decides what goes to the client.
- AI agent for customer supportAnswers customers from approved information, checks order status in your systems and hands over to colleagues the cases that need a person.
- AI agent for lead qualificationAsks the qualification questions agreed with your team, scores each lead against the agreed criteria and sends it to the right person.
- AI agent for researchGathers information about the market, competitors or suppliers from approved sources, with citations for every claim, while the analyst validates the conclusions.
- AI agent for document processingTakes in incoming documents, extracts the data, checks it against your rules and systems and sends it on, with a person handling the exceptions.
- AI agent for financial reportingPrepares periodic reports from your financial and operational data and flags variances, which the finance team then analyses.
- AI assistant for recruitmentSupports recruiters with CV screening, interview scheduling and candidate communication, without any rejection decisions taken automatically.
- AI assistant for e-commerceGuides shoppers to the right product using your catalogue, answers questions about availability and orders, and prepares cart recovery messages only where consent exists.
- AI agent for operationsTracks internal requests, tickets and stock thresholds, prepares tasks for teams and coordinates handovers between departments, with a person responsible for every decision.
- AI agent for data analysisYou ask a question about your company's data in natural language, and the agent writes the query, runs it on authorised sources and explains the result, showing how it got there.
- AI assistant for your internal knowledge baseEmployees ask how something is done in the company and get the answer from internal procedures and policies, with a reference to the source document.
- AI agent for workflowsRuns multi-step processes that need decisions along the way, where fixed automation stops at the first exception, with human approval at the sensitive points.
- Multi-agent systemsSeveral specialised agents, each with its own role, tools and permissions, coordinated in a single process and supervised by a person. Only where a single agent is no longer enough.
02 / 04
LLM & custom AI
Language models connected to your company documents and data, with access control and evaluation of the answers.
- LLM integrationLanguage-model features added to the applications and processes you already use, with the model chosen for cost and confidentiality.
- Custom AI assistantsAssistants built for a specific role — quoting, in-house legal, technical support — with that role's tone, rules and sources.
- RAG systemsAssistants that search the configured sources before answering and show where each piece of information comes from.
- Enterprise knowledge basesThe infrastructure that keeps company knowledge in order: inventoried sources, permissions, updates and an owner for each domain.
- Semantic searchSearch by meaning across your website, catalogue or documents: relevant results even when users do not type the exact words.
- Intelligent document processingThe engine that extracts, classifies and summarises documents in batches and delivers structured data, ready to review and import.
- AI API integrationConnecting AI providers' APIs to your systems, with keys kept on the server, limits, logs, cost control and a fallback provider.
- AI evaluation and monitoringTest sets, checks at every change, human spot-check reviews and cost tracking, so you know how your AI performs over time.
03 / 04
Voice agents
Calls answered, appointments confirmed and conversations summarised, with callers informed and transfer to a person.
- AI receptionistYour company's main line answered politely: simple questions handled, messages taken and calls routed to the right person.
- AI voice agent for inbound callsThe first line for high volumes of support and order calls: caller identification, answers from approved sources, a ticket created and a transfer with context.
- AI voice agent for outbound callsConfirmations, reminders and follow-ups called automatically, only to people you have a relationship with and a clear legal basis for contacting.
- AI phone bookingBookings, rescheduling and cancellations made by phone directly in your live calendar, with a confirmation sent to the customer.
- Voice lead qualificationThe first qualifying questions asked by phone, right after a lead asks to be contacted, with the record completed for sales.
- Phone conversation analysisCalls transcribed, summarised and grouped by topic, so you can see why customers call and where the service can improve.
04 / 04
Computer vision
Images and video analysed for well-defined tasks: counting, inspection, events — with no biometric identification by default.
- Object detectionModels that recognise the objects that matter to your process in images and pass them on as structured data.
- People and object countingAnonymous counting of crossings, zone occupancy or the items in a batch, without identifying anyone.
- Industrial visual inspectionCameras on the production line flag parts with visible defects, and the operator confirms every rejection.
- Video event detectionVisual rules that flag entries into restricted zones, missing protective equipment or fallen objects, for human review.
- Video analytics for retailAggregated visitor flows, queue length and empty shelves from in-store cameras, without identifying customers.
- Operational monitoringVisual tracking of process stages and of vehicle and pallet movement in yards and warehouses, so you can see where the flow gets stuck.
- Edge AI for computer visionVideo analysis on devices installed on site: fast response, less network load and images that never leave the building.
- Licence plate recognitionAutomatic reading of licence plates at gates, barriers and car parks, with clear rules on access, retention and human review.
- Visual smoke and fire detectionAn additional warning layer that spots smoke and flames in camera images and quickly alerts the people who can check.
- Fall detectionCameras that notice when a person falls and does not get up, so an alert quickly reaches someone on the team who can help.
- Drone detectionCameras and models that spot drones appearing over a site, track them in the frame and alert the security team.
- Container code recognitionAutomatic reading of ISO 6346 codes on containers, with check digit validation and direct transfer to the terminal system.
- Nameplate readingYou photograph the nameplate of a motor or piece of equipment, and its data reaches your inventory or ERP sorted into fields.
- Crack detectionModels that find and outline cracks and surface defects in photos and drone imagery, ready for an engineer to review.
- Car park monitoringOccupancy of every parking space or zone, read from cameras, with free-space counts kept up to date and no identification of drivers.
- Livestock monitoringCameras and AI that count animals, follow activity in the barns and flag to the farmer the behaviour worth a closer look.
- Vehicle traffic analysisAnonymous counting and classification of vehicles by direction, at gates, on access roads or on building sites, with data aggregated by interval.
- Video synopsisHours of footage condensed into a short summary of activity, searchable by object type, zone and time range.
- Custom computer vision modelsWe develop computer vision models for your task end to end: data, labelling, training, evaluation, optimisation, deployment and retraining.
The principles we build by
Human in the loop
Decisions with impact stay with people. The agent proposes, the team approves.
Least access needed
Each system gets only the permissions it needs for its task.
Data handled with care
We establish which data reaches AI providers, on what basis and for how long it is kept.
Evaluation before launch
We test on real examples and agree the indicators we track afterwards.
Transparency
Users know when they are talking to an automated assistant and can reach a person.
Limits stated clearly
We explain what the solution cannot do, not just what it can.
Questions about AI
Where do I start if I don't know which AI solution suits me?
With the process, not the technology. You tell us which activity takes up the most time or where delays occur, and we assess whether AI helps, what data is needed and which option makes sense. Sometimes the right answer is a simple automation, without AI.
What is the difference between a chatbot and an AI agent?
A chatbot answers questions based on a script or a text. An AI agent follows a workflow: it understands the request, looks up information in approved tools (CRM, calendar, documents) and prepares or carries out concrete steps, with clear permissions, an action log and human approval for important steps.
What is RAG?
RAG (Retrieval-Augmented Generation) is the method by which an AI assistant first searches the company documents it is allowed to use and only then writes the answer, with a reference to the source. It increases relevance and allows verification, but it does not eliminate every error, which is why uncertain answers are flagged for the team.
Does AI replace people on the team?
That is not the aim. The solutions take over repetitive tasks and prepare information, so your team has more time for activities that need judgement, empathy and experience.
What happens to company data?
During the analysis we establish which data is used, where it is processed, which providers are involved and with what guarantees, who has access and how long it is kept. Sensitive data can be excluded or anonymised where possible.
What does the system do when it doesn't know the answer?
We configure it to say that it does not have enough information, to ask for clarification or to transfer the request to a person, instead of making up an answer.
How can I quickly find out whether AI can help me?
You can take the online AI assessment: eight multiple-choice questions about your team's activities. At the end you see which solutions might be relevant, what still needs to be analysed and what the next step is. It is a preliminary assessment, which we can explore further together.
How much does an AI project cost and how long does it take?
It depends on the complexity of the process, the quality of the data, the integrations needed and the level of control required. After the initial analysis we can propose a reasoned estimate and, often, a small first step that is easy to evaluate.
Can’t find the answer? Write to us and we’ll reply directly.
Have a process that could run faster?
Tell us which activity slows you down. We assess whether an AI solution makes sense, what data is needed and what the first step would be.