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A NEW CHAPTER

Magical is now backed by Shiva.

Shiva, founded by Lucas Marques, former COO of Méliuz, invests in companies built with artificial intelligence. We share a vision: turning the potential of AI into real results for every client.

Shiva

Venture capital
Founded by Lucas Marques

BEHIND SHIVA

MonasheesEndeavor Catalyst

Leading funds that invest in Shiva.

Read in Brazil Journal

AI applied to industrial distribution

Protect margins across parts, inventory, sales and delivery.

Industrial distribution combines technical catalogs, tied-up capital, consultative sales and logistics commitments. Magical organizes context and exceptions so salespeople can respond faster while keeping availability, cost and margin in view.

Magical Applied AI consulting for Industrial distribution Brazil

Industrial parts organized along warehouse aisles

Evidence

At Profil, forwarding orders to production went from up to 72 hours to minutes.

View the case study

Operational workflow

03 / Industrial distribution

  1. Demand
  2. Purchasing
  3. InventoryInventory does not translate into forecasts
  4. Technical salesRight part, slow response
  5. ShippingDelivery has to correct the sale
  6. After-sales

Where operations lose margin

Right part, slow response

Salespeople rely on catalogs, memory and internal queries to prepare proposals.

Signal: Long response times and knowledge concentrated in a few people.

Inventory does not translate into forecasts

Turnover, stockouts and purchasing compete without a shared view of demand.

Signal: Excess slow-moving items and shortages of critical parts.

Delivery has to correct the sale

Deadlines, documents and availability change after the promise is made.

Signal: Rework across sales, parts and logistics.

Where we start

Related experience

Projeto em destaque · Manufacturing

Profil

Less waiting between sales and production, with automated CRM records and quotes.

Up to 72 h → minutes

from signed order to production entry

View the case study for Profil

How we turn an opportunity into results

  1. 01

    Understand the operation

    We interview decision-makers and operators to map processes, data, exceptions and costs before suggesting tools.

  2. 02

    Choose where to start

    We prioritize an opportunity by expected return, feasibility and risk. We agree on responsibilities and how to measure results before starting.

  3. 03

    Put it to work

    We implement, monitor real usage and measure process changes before expanding the portfolio.

Governance from the first workflow

Frequently asked questions

Does AI replace the technical salesperson's expertise?

No. It organizes catalogs, history and rules to make knowledge more accessible and leave exceptions to the people who understand the application.

Is an ecommerce operation required?

No. Initial workstreams can operate within internal sales, parts, procurement or shipping workflows.

How do you handle SAP, TOTVS or legacy systems?

Integration is chosen after understanding the workflow. APIs, exports, controlled read access and interface automation are options, not assumptions.