For SMBs & mid-market

Secure company AI that speeds up processes and takes pressure off teams.

We help SMBs and mid-market teams introduce AI securely and productively, from opportunity analysis to AI workspaces, knowledge access, and automation with real day-to-day value.

Secure setupsBuilt on existing ITClear entry pricing
Clear for decision-makers
Productized instead of agency-shaped
Secure setups over tool hype
Built around real operational work

No diffuse AI consulting. Just clear entry points with real value.

We help companies choose the right AI entry point in a way that is understandable, secure, and commercially sensible. That turns AI complexity into a clear first step with real business value.

01

A clear starting point instead of AI chaos

We show where AI genuinely makes sense in your business, with clear priorities, effort, and the next concrete step.

02

Introduce it securely into existing IT

We bring AI into your current environment in a way teams can actually use, controlled, traceable, and without tool sprawl.

03

Make value measurable in a pilot

We launch an initial use case in a controlled way so time savings, relief for teams, and business value become visible.

companies looking for a clear AI starting point instead of long consulting projects
teams with sensitive data that want a secure, controlled rollout
decision-makers who want to assess value, effort, and risk clearly

Three clear offers for secure company AI

From the first step to secure usage and productive implementation — understandable, controlled, and tied to clear business value.

Stage 1 · Entry & prioritization

from EUR 3,490

AI Opportunity Sprint

Workshop to prioritize realistic AI use cases, risks, and the next concrete steps.

Studies show that for well-selected AI tasks, teams worked 25.1% faster and delivered more than 40% higher quality. That underlines why clean prioritization matters before implementation starts.

Clear priorities instead of idea listsRealistic 30/60/90-day roadmapClean transition into implementation

Stage 2 · Secure internal usage

from EUR 3,900 setup

Secure AI Workspace

A secure internal AI environment for teams with clear roles, governance, and a clean setup.

Studies show that 78% of AI users bring their own AI tools to work. A secure AI workspace reduces shadow IT and creates a controlled foundation for productive use.

Secure entry instead of shadow ITClear roles and accessFoundation for productive internal AI usage

Stage 3 · Productive implementation

from EUR 12,900

AI Assistants & Workflows

Productive AI support for one clearly scoped business process — from assistant use cases to workflow logic.

Studies show that in service-heavy and process-oriented areas, GenAI can unlock 30–45% productivity potential.

30–45% productivity potentialFewer manual handoffsFaster day-to-day workflows

From the right starting point to productive implementation

Not every company starts in the same place. Depending on the situation, we begin with a sprint, a secure setup, or a clearly scoped first implementation project — and expand from there in a controlled way.

01

1. Clarify the starting point

We define the most sensible way to start — for example through an opportunity sprint or directly through a clearly scoped first project.

02

2. Build the foundation

We put the right basis in place: secure usage, AI-ready knowledge, or a first clearly scoped use case.

03

3. Put it into productive use

The team works with a real day-to-day use case — secure, understandable, and with clear value instead of demo effect.

04

4. Controlled expansion

Based on the first results, we expand into more teams, knowledge areas, or processes — with clear prioritization instead of actionism.

Company AI should not live in a grey zone

Whether the entry point is a sprint, a workspace, or a first implementation scope, roles, access, operating model, and core governance are considered from the start.

Security is the prerequisite for teams to use AI meaningfully and responsibly in day-to-day work.
clear handling for sensitive data instead of public chat experiments
roles, permissions, responsibilities, and AI governance are defined early
the setup fits your actual IT reality

With a view to governance, AI literacy, and documentation in the spirit of the EU AI Act.

In your cloud
Self-hosted
Managed as a pragmatic entry

Typical use cases with fast, measurable business value

These typical use cases show where secure company AI often creates value quickly and which effects have already been measured in similar fields of work.

Sales

Make proposal knowledge, meeting preparation, and internal research more accessible.

Typical value

25.1% faster handling and 12.2% more output

Typical starting point

Typical starting point: Make knowledge AI-ready or AI Opportunity Sprint

Marketing

Deliver content, campaigns, and knowledge reuse faster and with more consistency.

Typical value

Practical examples show 30–40% higher productivity in content and email marketing workflows.

Typical starting point

Typical starting point: AI Assistants & Workflows or Secure AI Workspace

Operations

Make recurring handoffs, document work, and manual steps cleaner and faster.

Typical value

More than 25% shorter handling times in service-heavy and process-oriented workflows

Typical starting point

Typical starting point: AI Assistants & Workflows

Support

Speed up answers and make internal knowledge useful for recurring questions.

Typical value

14% higher productivity on average; in examples such as Klarna, AI assistants also handle a large share of standardized service contacts.

Typical starting point

Typical starting point: Make knowledge AI-ready or AI Assistants & Workflows

Internal knowledge

Turn PDFs, folders, and scattered team knowledge into one understandable access layer.

Typical value

Up to 40% less time and 18% higher quality

Typical starting point

Typical starting point: Make knowledge AI-ready

Entry & prioritization

See quickly where AI makes economic sense and which first scope is actually the right one.

Typical value

Prioritize where studies have observed 12.2% more output and 25.1% faster handling

Typical starting point

Typical starting point: AI Opportunity Sprint

Early references and practice examples

The examples below are illustrative snapshots of what typical Salty Labs entry projects can look like.

Internal knowledge access for service and operations

Distributed PDFs, instructions, and process knowledge were turned into an initial usable internal knowledge layer.

What changed?

Faster answers to recurring questions and less search effort in daily work.

Secure AI Workspace for a sensitive team setup

A public tool mix was replaced by a cleaner internal AI access point with roles and usage logic.

What changed?

More control, fewer grey zones, and a more productive starting point for the team.

Pilot for a recurring document-heavy workflow

One clearly scoped process was modelled and implemented as a first productive automation pilot.

What changed?

Fewer manual handoffs and a stronger basis for a credible business case.

The team behind Salty Labs

Strategy, product, and technical implementation in one team — with experience from enterprise delivery, venture building, and practical hands-on execution.

We do not set up anything we have not already built, used productively, or tested in real workflows ourselves. That is why our advice is not theoretical, but grounded in implementation.
Portrait of Stefan Hain

Stefan

Strategy, Product & AI Implementation

MBAI · PSPO I · PSM I · 10+ years in product and strategy

Connects business, tech, and UX and translates AI topics into clear use cases, roadmaps, and implementable product logic.

Portrait of Timo Rogge

Timo

CEO, Growth & Commercial Execution

Engineering understanding · Business development · Venture building

Connects business development, partnerships, and operational execution so technology becomes a viable commercial model.

Portrait of Chris Meinl

Chris

CTO & Technical Implementation

8+ years in software engineering and architecture · CTO/tech co-founder · 15,000-user product

Leads the technical delivery of stable, scalable AI solutions — from infrastructure and integrations to productive rollout.

What we recommend is not just something we designed on slides — it is something we have already built, used, or operationally tested ourselves.

Common questions before getting started

Do we already need perfectly structured data?

No. To get started, a clearly scoped knowledge area or one defined process is usually enough. In the AI Opportunity Sprint, we make visible: - what is already usable immediately and - what should be prepared first. Clean data helps later, but it is not a barrier to entry.

Do we need to be technically strong already?

No. The offers are intentionally built so non-technical decision-makers can understand and buy them. We only bring in technical complexity - where it is genuinely needed for security, integration, or impact. What matters most is having one contact person in IT — we handle most of the technical detail work.

Can this run in our existing IT environment?

Usually yes. We work on top of your existing IT stack (for example M365 and current tools) and choose solutions - that are suitable for the DACH context, - take EU hosting / GDPR into account, and - fit sensibly into your landscape. That is why we clearly separate software, setup, and operations and discuss security and hosting early.

Is this also relevant for small and mid-sized companies?

Yes — especially for them. SMBs and mid-market companies benefit most from clearly scoped, fixed-entry offers because they do not want months of consulting; they want visible results within 30–60 days. Our offers are shaped to require manageable internal effort and provide clear next steps — without needing an in-house AI team.

How much internal effort is required from our side?

For a typical start, you usually need: - 1–2 responsible people (for example leadership / business owner + IT), - a small number of workshops or check-ins, and - some time for feedback and testing. We handle most of the concept work, setup, and implementation. The goal is productive first results without disrupting day-to-day business.

Why are prices visible publicly?

Because pricing clarity builds trust. The visible prices are entry prices with a defined scope and help you understand - expected effort, - offer depth, and - a realistic budget frame. Any additional scope is offered transparently as an add-on module — not hidden later in the process.

Do we always have to start with the AI Opportunity Sprint?

No, but it is the standard entry point. The sprint is ideal when priorities and the target picture are still unclear. If there is already a clearly defined and tightly scoped need, we can also start directly with: - a Secure AI Workspace setup or - a concrete AI assistant / workflow project. What matters is that the entry stays understandable, manageable, and clearly bounded.

What is the difference between workspace, knowledge, and AI Assistants & Workflows?

Secure AI Workspace creates a secure AI workplace for teams with roles, governance, and access logic. Make knowledge AI-ready structures company knowledge so AI can work with it meaningfully. AI Assistants & Workflows implement concrete assistants or workflows for clearly scoped business processes — with direct impact in day-to-day work, for example in sales, support, or operations. That allows us to move step by step instead of trying to do everything at once.

What happens concretely after the AI Opportunity Sprint?

After the sprint, it becomes clear: - which use cases are actually worth pursuing, - which first implementation path makes sense, and - what a 30/60/90-day plan looks like. Typical next steps are: - a Secure AI Workspace setup as a safe foundation, - a knowledge setup for one important area, or - a first AI assistant / workflow with a clearly defined scope. There is no hidden obligation to move into a large transformation — you decide the next step.

How do you address privacy, security, and the AI Act?

We do not sell legal advice, but we do make sure the introduction is clean and documented: - clear policy building blocks for internal usage, - role and access logic, - documentation support for privacy and IT security, and - consideration of AI literacy requirements such as enablement and training. That makes it much easier for you to represent security, privacy, and governance internally — without having to invent everything from scratch.

Are we tied to specific tools or providers?

No. Salty Labs is not a proprietary platform product. We work with proven, often EU-hosted solutions and choose what fits best with: - your existing IT, - your compliance requirements, and - your budget. What matters to us is that you are not locked into us, but end up with a solution you can continue to operate.

Do you only advise, or do you actually implement as well?

We come from practical implementation and we: - build setups ourselves, - support go-lives, - see real usage inside teams, and - rely on things we have already tested productively. We do not recommend anything we have not already built, used, or integrated into real workflows ourselves.

Find out which setup makes sense for your company

In a non-binding 30-minute conversation, we clarify whether an AI Opportunity Sprint, a Secure AI Workspace, or a first AI assistant / workflow is the most sensible entry point for your company. You briefly describe your situation — we help assess potential, effort, and a realistic first step.

Prefer to reach out by email? Send us a short note with your context, team, and preferred entry point at [email protected].

You can select a suitable time directly through our external booking service. For privacy reasons, we only load the calendar after you deliberately open it.

  • which area should benefit first (for example sales, support, operations)
  • which data or systems are involved
  • whether the main priority is security, knowledge, or automation