For energy companies

Make AI productive where your energy company loses time today.

In maintenance documentation, project delivery, internal processes, or sales, we bring AI securely into existing workflows in a way decision-makers can understand and that fits your IT.

25%

faster to results

40%

better results

15%

more productive output

Vattenfall logo
Statex logo
Kold Shapes logo
GoSalty logo
LocaMarine logo
PrimeSurf logo
Tomorrow logo

You want to use AI meaningfully in your energy company. But there is still no clear starting point.

Between tool hype, manual handoffs, and unclear processes, what is usually missing is the first concrete step that actually fits the organization.

Unclear AI starting point

Whether it is grid planning, maintenance, sales, or project delivery, the highest-leverage starting point is often still unclear.

Tool mess instead of clear structure

Individual teams use ChatGPT or Copilot on their own, without governance, without visibility, and without a secure structure.

Too much manual work

Maintenance logs, project reports, and technical documentation are still created, compiled, and passed on manually in too many places.

Knowledge exists, but is not quickly usable

The knowledge of experienced technicians, project leads, and planners sits in people's heads, legacy documents, and fragmented storage locations, and gets lost when people leave.

Salty Labs turns AI pressure into a secure and productive entry point.

We introduce company AI in a way teams can understand, justify, and use in day-to-day work. Clear for decision-makers, cleanly prioritized, and aligned with the real IT situation.

Define the right starting point

We clarify whether prioritization, a secure workspace, or a clearly scoped pilot is the most sensible first move.

Bring it securely into existing IT

We set up AI so roles, access, data handling, and operating model fit the environment you already have.

Make it productive step by step

We move the first use case into controlled usage so impact, effort, and the next expansion steps become visible.

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

Our offers

From the first AI workshop to productive implementation in your processes.

Stage 1 · Entry & prioritization

AI workshop / AI Opportunity Sprint

We work with you to identify where AI really makes sense in your energy business, prioritize the most relevant use cases, and define the next steps.

Clear priorities instead of idea listsRelevant use cases instead of gut feelingConcrete 30/60/90-day roadmap

Stage 2 · Secure company GPT

Secure AI usage for teams

We create the foundation teams need to use AI securely, in a controlled way, and in line with the existing IT setup in day-to-day work.

Secure entry instead of shadow ITClear roles and usage rulesFits your existing IT

Stage 3 · Productive implementation

AI integration for concrete processes

We bring AI into productive use where real value appears in functions and processes such as grid planning, maintenance, sales, or project delivery.

Focus on real processesLess manual workFaster day-to-day workflows
Make knowledge AI-ready
Data sources and internal knowledge structure
Special setups on request

What concretely improves in day-to-day work

Not in abstract terms, but in faster workflows, less manual work, and more usable knowledge — exactly where teams lose time every day or friction builds up unnecessarily.

Faster to results

Recurring tasks, preparation work, research, and internal answers become more structured and significantly faster.

Measured effect

Up to 25.1% faster completion and 12.2% more output

Accelerate and automate processes

Recurring workflows, handoffs, and process steps become more structured, significantly faster, and automated where it makes economic sense.

Measured effect

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

Make knowledge usable faster

Information from PDFs, repositories, team knowledge, and existing systems becomes easier to find and more usable in day-to-day work.

Measured effect

Depending on the task, up to 40% time savings and noticeable quality gains

How our clients get started with AI

Concrete examples from current projects — without company names, but with real outcomes.

From first use cases to productive company AI in four clear steps

No long-term project, no experimentation lab. We start where it creates the most value for you — and expand from there in a controlled way.

01

Identify the highest-value opportunities

We analyze together where AI has the biggest leverage in your company — and what is realistically achievable.

Typical: 1–2 days

Afterwards you have: Prioritized use cases, a clear roadmap, and a decision-ready next step

02

Build a secure foundation

We set up a secure AI environment — with roles, governance, and a clear operating model that fits your IT landscape.

Typical: 2–3 weeks

Afterwards you have: A productive AI setup with clear rules for your team

03

Make the first solution productive

We implement a concrete AI assistant or workflow — for a clearly scoped process with measurable value.

Typical: 4–6 weeks

Afterwards you have: A productive AI application in real day-to-day work

04

Scale in a controlled way

Based on the first results, we expand into more teams, processes, or knowledge domains — with clear prioritization.

Typical: Ongoing

Afterwards you have: A growing AI system that scales with your company

Security is built into every step

Roles, governance, data protection, and the operating model are built in from the start — not bolted on later.

Roles and access logic from day one
Governance and usage rules in the setup
Fits your existing IT
Book an intro call

We will show you where your best starting point is.

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 Hain

Strategy, Product & AI Implementation

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

Translates AI opportunities into clear use cases, roadmaps, and implementable product logic, with experience across offshore wind, renewables, and utility-scale projects, including Vattenfall, Deutsche Windtechnik, and SMA.

Portrait of Timo Rogge

Timo Rogge

Growth & Commercial Execution

Engineering understanding · Business development · Energy industry experience

Connects technical understanding, business development, and operational execution, with project experience at Vattenfall and LichtBlick as well as exposure to offshore wind, battery storage, and collaboration with municipal utilities.

Portrait of Chris Meinl

Chris Meinl

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.

How do we clarify scope and effort?

In the first conversation, we clarify which entry point makes sense for your situation and how large the initial scope should really be. We look at: - the target picture, - the teams involved, - technical constraints, and - the most realistic next step. That keeps the entry understandable and clearly bounded before a concrete implementation scope is defined.

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 AI setup makes sense for your energy 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 grid planning, maintenance, sales, or operations)
  • which data or systems are involved
  • whether the main priority is security, knowledge, or automation