AI for business

    Putting AI to work in your SME

    Answering customers, preparing quotes, entering orders, finding the right procedure: part of these tasks can be prepared by AI. Together we identify where it saves time, we set it up on your data, and your teams keep the decision.

    Identify your use cases — 30 minutes
    Our first offer

    An AI installed in your company, without the cloud

    Your know-how gathered in a knowledge base, the language model that uses it and the tools built on it: everything runs on a machine in your premises. Here is what we install, how your teams access it, and how to choose between local and cloud.

    Read the full page

    Your data, an orchestrator, specialised agents

    Your data is brought together in a data lake. An orchestrator relies on a RAG to find the right information, then hands each task to the specialised agent. You keep the decision.

    Your sourcesAccounting · ERPCRM · salesEmailsDocuments · PDFWebsite · formsProduction · sensorsData lakeon your premisesOrchestratorRAGyour documents, citedSpecialised agentsQuote agentAccounting agentCustomer support agentPlanning agentQuality agentThey prepare, you approve

    The data lake

    A single reservoir that receives a copy of all your data, as it is.

    Today your information is scattered: accounting in one tool, customers in the CRM, exchanges in emails, procedures in PDFs. The data lake brings it together in one place, so the AI has a single point of access.

    • Installed on your premises: your data does not go to the cloud.
    • Fed automatically: your current software stays in place, nothing changes for your teams.
    • Figures and documents kept as they are, with the same access rights as today.

    RAG

    Retrieval-Augmented Generation: answers generated from a search across your documents.

    An AI model does not know your documents. RAG splits them into passages and indexes them by meaning, not just by words. For each question, it finds the relevant passages and hands them to the AI, which answers from them.

    • Answers grounded in your sources, with a reference to the document cited.
    • Always up to date: a new document counts as soon as it is indexed, with no retraining.
    • Fewer inventions: if the information is not in your documents, the AI says so.

    How it works, step by step

    Example: a customer requests a quote on your website.

    1. Collection

      Your sources feed the data lake continuously: accounting, CRM, emails, documents, website forms.

    2. Indexing

      RAG indexes the written content (past offers, terms, product sheets). Figures stay in tables and are queried directly.

    3. Request

      The customer’s request arrives through the website form. It could also come from an email or a question from your teams.

    4. Orchestration

      The orchestrator understands the request. It fetches prices and the customer’s history from the data lake, similar offers through RAG, then hands the task to the quote agent.

    5. Preparation

      The quote agent drafts the offer and shows which documents it relied on. The other agents do the same for accounting, support, planning or quality.

    6. Approval

      A person reviews, corrects and approves: nothing goes out without you. Your corrections become examples for the next answers.

    What AI can do for your teams

    Sales and customer service

    Customer service and e-shop chat

    Already in production

    Your teams answer the same questions every day, without the customer's history in front of them.

    The AI shows previous exchanges, suggests a short reply in the customer's language, and prepares the hand-off to a quote or an order.

    Quote requests

    Every request means looking up the item, the price, the lead time and the customer's terms in several tools.

    The AI reads the request, finds the items and prices in your ERP and prepares a draft quote to validate.

    See the sales and customer service page

    Operations

    Orders received by e-mail or PDF

    Orders arrive in every format and are re-entered by hand into the ERP.

    The AI extracts the lines (items, quantities, dates), checks them and prepares the entry; an employee validates.

    Supplier invoices and purchasing

    Checking invoices against orders and comparing supplier offers takes hours.

    The AI matches invoices, purchase orders and receipts, flags discrepancies and compares purchase offers line by line.

    See the operations and orders page

    Engineering and quality

    Technical documentation

    The answer exists somewhere: product sheet, drawing, standard, manual, old e-mail.

    An internal assistant answers your teams' questions, citing the source document.

    Quality and certification

    ISO files, non-conformity reports, audits: a lot of writing and formatting.

    The AI prepares drafts from your data and your templates, and checks that nothing is missing.

    Passing on know-how

    One retirement, and part of the trade walks out the door.

    We structure the knowledge of key people (interviews, documents, histories) so that it stays searchable.

    See the engineering and quality page

    Management

    Steering and summaries

    The figures are in the ERP, the accounts and the spreadsheets, but the summary takes time.

    Every week the AI prepares a summary of your indicators and points of attention, ahead of your management meetings.

    See the management and steering page

    How we work

    1. 1

      Use-case mapping

      Half a day with your teams to spot repetitive tasks and measure what they cost.

    2. 2

      Choosing a first case

      The one with the best ratio between time saved and set-up effort.

    3. 3

      Prototype on your real data

      Your items, your customers, your documents. Not a generic demo.

    4. 4

      Go-live

      Connection to your tools (ERP, e-shop, e-mail), user access, monitoring.

    5. 5

      Continuous improvement

      Users report what is missing, we fix it and we measure. Then the next case.

    Your data stays under your control

    Depending on your needs and how sensitive your data is, two paths:

    Custom-built, installed on your premises

    The language model, the database and your business data run on a machine installed in your premises. Nothing is stored or processed outside.

    BeMyTalent, data in the EU

    Our management suite, designed and operated in Switzerland, with data hosted in the European Union and partitioned per project. AI prepares, you validate.

    In both cases, you remain the owner of your data and of what has been built.

    AI and data protection (Swiss FADP)

    Our principles

    • AI prepares, your teams decide.

      Nothing is sent to a customer without human validation.

    • We measure before adding.

      Every roll-out comes with simple indicators: time saved, usage rate, errors avoided. And we also tell you what does not work yet.

    • We start from your business, not from a tool.

      We do not sell a platform: we choose the technology according to the problem.

    • We stay after go-live.

      An AI improves with use, not only at launch.

    Why Ekylibr

    Ekylibr is a strategy and development consulting firm based in Neuchâtel. We support SMEs in their growth and build our own business software. We speak the language of management as well as that of the workshop, and we know the tools and constraints of the region's SMEs.

    Frequently asked questions

    Where do we start?+

    With a single process, repetitive and well defined. The mapping helps choose the one that pays off fastest.

    Do we have to send our data to the cloud?+

    No. We can install everything on your premises. With BeMyTalent, data is hosted in the European Union and partitioned per project.

    What hardware is needed for an on-site installation?+

    A dedicated unit, the size of a small desktop computer, installed on your network and sized to your volume.

    Is it compatible with our ERP?+

    We connect to your existing tools through their exports or interfaces. The mapping checks what is accessible.

    How long before a first result?+

    A few weeks between the mapping and a first prototype on your data. The mapping sets the exact timeline for the chosen case.

    What about the Swiss data protection act (FADP)?+

    Custom-built, your data stays on site; with BeMyTalent, it is hosted in the EU and partitioned per project. In both cases, we document what is stored, where and for how long.

    How much does it cost?+

    On quotation, after the mapping: it defines the scope, the connections and the time required.

    Where could AI save you time? Let's talk for 30 minutes.

    No commitment. We will tell you where AI can help — and where it cannot.

    Book a slot

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