DATIFY

Who DATIFY is for

Wherever records live in spreadsheets and deadlines in someone’s head.Accounting firms, hauliers, manufacturers, property managers and public offices – a different agenda every time, the same starting point. Pick by the size of your organisation or by field and see what DATIFY takes over.

By field

Where DATIFY saves the most manual work

Each field shows what it keeps in DATIFY and how the assistant and automation work over it.

  1. Accounting and advisory firms

    Typical data sources
    • Contracts
    • Invoices
    • Filing deadlines
    • Clients
    • Incoming documents

    Dozens of clients, hundreds of documents and deadlines that cannot slip.

    Every client has their own folder with documents, dates and an owner. When an invoice or an amendment arrives, it is extracted straight into the row and it is clear who has to review it.

    • Extraction of invoices and contracts instead of retyping
    • Filing dates and deadlines watched by automation
    • Client data separated by roles

    „We did not want invoices to be merely stored. We needed to know who has to review them and what state they are in.“

    Pavla Šulcová · WC ServisRead the case study

  2. Transport and logistics

    Typical data sources
    • Fleet
    • Jobs
    • Insurance
    • Drivers
    • Servicing and repairs

    Vehicles, drivers, services and insurance that all overlap.

    A vehicle stays together with its driver, service jobs, insurance and the cost per department. A rule watches the dates, so an expiring inspection does not surface out on the road.

    • Inspections, service and insurance with advance reminders
    • Vehicle assigned to a driver, history included
    • Cost per vehicle and department in one overview

    „We have been with DATIFY almost from the start. What began as a record-keeping tool grew into a shared workspace for our jobs, contracts, vehicles and operational feedback.“

    The ČD Bus teamRead the case study

  3. Manufacturing

    Typical data sources
    • Machines
    • Inspections
    • Training
    • Spare parts
    • Complaints

    Assets, inspections and training where proof is mandatory.

    A machine carries its documents, inspections and the people allowed to operate it. During an audit nobody hunts for who confirmed what – the history stays with the record.

    • Machine record with documents, inspections and maintenance
    • Training and medical checks watched by a rule
    • Change history on every record

    „We are rolling DATIFY out to further parts of the group step by step and bringing new users on board.“

    Zuzana Revilaková · Pivovary Lobkowicz GroupRead the case study

  4. Retail and trade

    Typical data sources
    • Suppliers
    • Branches
    • Orders
    • Price lists
    • Complaints

    Supplier contracts, branches and framework deals with renewal dates.

    A framework contract stays with its supplier, price list and the branch it covers. Before the notice period runs out a rule speaks up, not the sales rep at a meeting.

    • Contracts with notice periods under watch
    • Overview by branch and department
    • Order approvals through a confirmation step

    „We were looking for a solution for records we had been keeping in various spreadsheets, emails and shared folders. We needed to bring them into one place and keep them easy to navigate at the same time.“

    Michaela Krýchová · data analyst, DOBROVSKÝRead the case study

  5. Property management

    Typical data sources
    • Buildings
    • Units
    • Leases
    • Meter readings
    • Inspections

    Buildings, units and tenancies linked together.

    A building knows its units, a unit knows its lease and the lease knows its dates and meter readings. Occupancy and revenue are counted from the records, not from a hand-kept spreadsheet.

    • Relations building → unit → lease
    • Lease, inspection and meter reading dates
    • Occupancy and revenue overviews

  6. Public sector and state organisations

    Typical data sources
    • Directives
    • Contracts
    • Assets
    • Requests
    • Meeting minutes

    Records where you must prove who changed what and when.

    Directives, contracts and assets carry a version, validity and an owner. Material for an inspection is assembled from the records rather than from e-mail and shared drives.

    • Traceable history on every record
    • Access governed by roles and permissions
    • Data in the operator’s own data centre
By type of agenda

What people put into DATIFY first

Agendas are built from the same parts: a table, dates, documents and the people around them. These are the ones clients start with.

  • Contracts and dates

    Contracts, amendments and notice periods with a reminder in advance.

  • Fleet

    Vehicles, drivers, inspections, servicing and insurance in one place.

  • Inspections and assets

    Machines and their paperwork, where proof is mandatory.

  • Documents and extraction

    Invoices and contracts land in the table without retyping.

  • Clients and jobs

    Who is accountable for what and what state it is in.

  • Controlled documents

    Version, validity and owner on every directive and policy.

Across every field

An agent works over the data, not a chatbot

The assistant does more than answer. It has its own access to the data, its own tasks in the calendar and reaches outside the chat as well – into a filter, a formula or an automation. This holds regardless of field or size.

Custom agents

An agent with standing instructions and its own access to data. Train it once and share it with colleagues like a new member of the team.

Tasks on a schedule

The Monday overview of contracts about to expire is prepared by the agent itself. Agree on it once and no reminders are needed.

Document extraction

An uploaded invoice or contract lands straight in the row, in batches as well.

Questions over the data

Ask in plain language and the agent goes through the records it has access to.

Generated documents

A report, a presentation or a table built from your data and attached to the answer.

AI outside the chat

A filter, a formula or an automation condition can be described in a sentence right where you need it.

An agent is a colleague whose work you can check

  • Its own permissionsIt reaches only the data you open to it. It does not borrow your access.
  • Traceable workThe history of runs and instruction versions stays with the agent, so its work can be reviewed.
  • Spending under controlTasks carry a spending cap, so the cost of AI stays within agreed limits.
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