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Enterprise AI

AI implementation that gets adopted, governed and run.

From assessment to operations: we prioritize your use cases, take the first one to production, train your teams with HackLab and run your AI with AI Management.

Implement AI in my company See HackLab training
adoption levels
3
adoption levels
hands-on with real cases
90%
hands-on with real cases
day roadmap
90
day roadmap
integrated strategy
1
integrated strategy

AI integration framework

How to implement AI in your company: 3 pillars and 4 layers.

Every AI integration rests on governance, processes and training, and each use case falls into one of four layers with its own % of efficiency, time saved and payback. This is how we shape every proposal: the three pillars at once, and each use case in the layer with the highest ROI and the lowest risk.

Enterprise AI integrationEnterprise AI that is visible, auditable and defensible
Business goals and KPIs

The three pillars move together or none of them moves: they are not phases, they are a system.

Pillar 01

Governance

What can be done, and who is accountable?

The decision and control framework that makes AI visible, auditable and defensible before your board or an auditor.

Who is accountable
CEO · cannot be delegated
How it is measured
% of AI tools in use that are approved

What we leave in place

  • A one-page AI use policy, signed by leadership
  • Data classified in three levels
  • Approved tools and who authorizes new ones
  • Investment and pilot kill criteria
  • An audit trail of AI-assisted decisions
  • A policy owner and a review date
See AI governance

Four implementation layers

Each layer raises the % of efficiency and time saved.

Every use case falls into one of these layers. Moving up raises the efficiency and the time you save on the task or process where AI is applied, but also the investment, the risk and the profile of who builds it.

↑ more efficiency · more investment · more risk · more technical profile

Efficiency and time saved in the process where AI is applied, not across the whole company. Layers do not add up.

Layer 01Payback in days

Assisted chat

A person talks to the model: asks, reviews and decides what to use. Nothing runs without someone reading it.

up to30%

Efficiency and time savedon the tasks where it is used

What your operations gain

  • Up to 40% less time on writing and analysis
  • Higher quality on the first try and less rework
  • Value from the first week, with no integrations
Investment
$
Risk
Low
Built by
Any employee

Examples: Résumé screening · Research and summaries · Document review · Employee onboarding

Which layer is each of your processes in?

In the assessment we place your use cases in the four layers, measure the baseline and build the path: fast returns in layers 1 and 2 while we build the pillars that layers 3 and 4 require.

AI adoption · HackLab

AI adoption: from curiosity to governed operations.

The training pillar, turned into a program: one strategy and three adoption levels. Less theory, more building on your company's real processes.

AI training for companies What Martí's leaders say
  4. ✓Governed, measurable and scalable AI

1 day · executive

AI for Leaders

Vision, priorities and governance.

  • Decisions and risks
  • Use-case prioritization
  • Guardrails
  • Human accountability

Every team leaves with

90-day AI adoption and governance roadmap

adoption levels
3
adoption levels
hands-on with real cases
90%
hands-on with real cases
day roadmap
90
day roadmap
integrated strategy
1
integrated strategy

Testimonials · HackLab AI Edition

Leaders augmented with AI.

The leadership team at Grupo Deportes Martí went through their HackLab AI Edition. This is what they say, in their own words.

Grupo Deportes Martí

Grupo Deportes Martí · Sporting goods retail · HackLab AI Edition

In Spanish, with Spanish captions

Tap a quote to hear it

Bambú, I believe, is playing a hugely important role in this. We are all truly very happy, and the team is genuinely excited about what we are doing.
Álvaro ArrigunagaCEO, Grupo Deportes Martí

They already took the step. Bring HackLab to your leaders and C-Level.

AI operations · AI Management

Once AI is adopted, someone has to run it.

AI Management runs your agents, measures usage, costs and the ROI of AI in every process, and keeps governance up to date.

  • Agent management

    Configuration, monitoring and evolution of AI agents.

  • Infrastructure and tokens

    AI usage measured, optimized and with costs under control.

  • Feasibility and ROI

    Technical and business feasibility before you invest.

  • Governance and guardrails

    Permissions, traceability and human validation.

  • AI automation

    End-to-end processes that run on their own.

  • Adoption and training

    Teams that build with AI from day one.

Success stories

AI that is already in production.

See all 11 cases

Frequently asked questions

Questions about implementing AI.

How do I implement AI in my company?

In five steps: an assessment that prioritizes use cases by value and feasibility, a quick win in production, your teams' adoption through HackLab, governance, and operations with AI Management. It all rests on three pillars (governance, processes and training) and starts with the AI layers that pay back fastest.

How do you measure the ROI of AI?

Every use case starts with a baseline, KPIs and ROI defined. The expected efficiency and time saved depend on the layer: up to 30% on tasks done with assisted chat and up to 80% of routine cases resolved by agents. Once in operation, AI Management measures usage, costs and results so you can decide what to scale.

What is AI Management?

It is the service that runs AI once it is adopted: management of agents, infrastructure and token usage, governance and guardrails, and feasibility and ROI assessment.

Can you implement the AI use cases that come out of HackLab?

Yes. The same team that facilitates HackLab designs and implements agents, automations and assistants, and then runs them with AI Management.

Enterprise AI services

Service layers

Where should AI start in your company?

Book an assessment and we'll prioritize your use cases, your HackLab or your first agent in production.

Book an assessment See success stories