Websky / AI dla firm
AI that understands the context. With a clear job to do.
We connect models with your company's knowledge, tools and processes. From a document assistant to an agent performing specific steps in a system — with control over quality, cost and access to data.
Applications
Start with the task,
not the model.
We begin with the task that takes time, requires searching for information or transferring data. Only then do we choose the model, sources and integration method.
01Company knowledge assistant
An employee asks about a product, procedure or terms of cooperation. The assistant searches approved materials for the answer, provides the source and flags any missing information. We prepare the documents, the search index and the access rules. We measure answer accuracy and the correctness of the cited sources.
02Documents and correspondence
AI recognises the document type, extracts the specified fields and prepares the data for the system. Validation checks formats, completeness and business rules. Ambiguous cases are handed over to a human. We measure field accuracy, the rate of corrections and document handling time.
03Sales and customer support
The assistant organises enquiries, identifies missing details and drafts replies using your product or service information. It can also prepare a CRM task. Prices and availability come from a specified source or are flagged for review. We assess the quality of the brief and the time your sales team needs to handle it.
04Agents connected to your systems
The agent carries out approved actions through an API or, where appropriate, the application interface. We separate reading data, preparing changes and applying them. Permissions, activity logs and approval steps are defined in advance. Success means completing the task correctly, not simply generating a response.
Workflow lab
From enquiry to order. AI for B2B sales.
Explore a B2B sales workflow: from a customer message to a quote, approval and a draft ERP order.
How we assess the value of an AI project
Measurement first.
Then scaling.
Baseline
We describe the current process, task duration, error types and data sources. We define test cases and success criteria.
Pilot on one process
We compare the AI result with the expected outcome. We also check difficult cases, refusal to answer, and handling of missing data.
Integration and development
We embed the solution into the team’s day-to-day work. We monitor quality, cost and response time. We update the sources and tests as the process changes.
An example of potential time savings
80 tasks per day × 3 minutes saved per task × 20 days = 80 hours per month. This illustration assumes a steady workload and net time savings after human review. The pilot will test whether these assumptions hold; the calculation is not a guarantee of results.
Architecture that fits your data
Cloud, on-premises
or hybrid.
The choice depends on your data, required response time, user numbers and running costs.
Source and access control
We define which documents and systems the assistant may use. User permissions also cover knowledge search. We set out rules for updating and deleting data.
Control over actions
We define which actions the agent can take and which permissions its service accounts need. Preparing a change and applying it are separate steps. Important updates and outgoing messages require approval and are logged.
Quality and running costs
We prepare a set of tests, usage limits and monitoring. We measure tasks solved correctly, not the number of conversations. For simple operations, we choose solutions whose cost matches the value of the task.
Project in progress · Switzerland
Praxisgemeinschaft
Spreitenbach.
On-premises AI to support a medical practice using Vitabyte/E-PAT. The project starts with a pilot involving one doctor and reception staff, followed by a rollout to ten doctors and the wider practice team.
Documentation and knowledge
Transcription, draft consultation notes, record summaries and search across approved materials. Authorised staff must review the results.
Reception and administration
Sorting correspondence and documents, preparing responses, and supporting task workflows. Access to information is based on the employee’s role.
Integration and oversight
Planned integration with Vitabyte/E-PAT through an API and, where needed, browser automation. Clinical actions require a doctor’s approval, and all operations are logged.
Project in progress. The description outlines the scope of work and does not confirm completion of all features or clinical results. AI supports staff and does not replace a doctor’s decision.
First step