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01Services

3 services, and what arrives with each.

Each service starts with the problem it solves and ends with what stays with you. Open the one that looks like your situation: the proposal shows the stages, what arrives, who from your team takes part and what starts being measured.

Data

Data Architecture and Governance

A number nobody disputes.

For whoever takes a number to the board and cannot say where it came from. We organise the data's path, from source to indicator, and deliver the data ready to use, with someone answering for every number.

What arrives

  1. A charter of indicators, with an owner and an origin for every number
  2. The automated check that fails the number when two sources disagree
  3. The ready data served through integration, agent access and a dashboard

How it is boughtOne project, from the assessment to assisted operation.

See the proposal

Culture

AI Culture and Operations

The whole company working with AI.

For a company that bought AI and saw it stay with the people who already knew how to use it. We take AI into the work of every area and every level, and hand the repetitive work of each role to an agent, with the decision kept by whoever approves.

What arrives

  1. A plan of tracks per area and per level
  2. An AI usage policy per area
  3. Agents running in each role's work, with the human decision kept where it is required

How it is boughtOngoing culture cycles, and a role-by-role agent project.

See the proposal

Products

Vibe Coding and AI-Based Products

An AI product that does not start from scratch.

For a company already building with AI in more than one area, where every application is born a different way. We write the standard the whole company builds to with AI, and build the core its AI products then run on.

What arrives

  1. A repository template every new application is born from
  2. The first application in production built to the standard, alongside your team
  3. An agentic core every new product reuses

How it is boughtTwo projects: the standard for building with AI, and the core for AI products.

See the proposal

02Markets

Markets we serve

The same services, applied to the data of one segment. Each market names who buys, the problem in the words of whoever answers for it, and the data we already know there.

  • Real Estate

    The portfolio is spread across the developer's system, the collector's spreadsheet and the administrator's report, and the three do not close on the same balance.

    Who buys

    • Real estate funds
    • Developers
    • Builders
    • Real estate agencies
    • Banks
  • Non-profit Sector

    Donations arrive through more than one payment gateway, and none of them talks to the donor base.

    Who buys

    • Non-profit organisations
    • Foundations and institutes
    • Fundraising leadership
    • Marketing and donor relations
  • Franchises and Multi-Unit Retail

    Each unit runs a different point of sale, or a different version of it, and the ERP and the stock do not close with the day's till.

    Who buys

    • Franchisors
    • Multi-unit franchisees
    • Food service chains: restaurants, dark kitchens, coffee shops and ice cream shops
    • Pet shop chains
    • and others