Discover What AI Can Really Automate in Your Business

Everyone tells you to "use AI", but nobody tells you where, how, or whether it will pay off. We answer that with skin in the game, we analyze your whole business, build your highest-return automation in two weeks, and you only pay if it proves profitable. Then we automate the rest. Honest advice from a team that builds and operates AI systems in production, not slideware.

What Our AI Consulting Covers

• AI Opportunity Audit: We go through your operations process by process and identify where AI genuinely fits, repetitive communication, document handling, decisions based on patterns, surveillance, data entry. And just as important, where it doesn’t fit, so you don’t burn budget on hype.
• Use-Case Feasibility & ROI: Each candidate use case gets a verdict, technically feasible or not, estimated build and running costs, expected savings, and payback period. You see the numbers before deciding anything.
• Data Readiness Assessment: AI is only as good as the data feeding it. We audit what data you have, where it lives, its quality, and what needs fixing before an AI project can succeed, often the most valuable part of the whole engagement.
• Model & Architecture Selection: Cloud APIs (OpenAI, Anthropic) or self-hosted open-source models on your own GPUs? Per-request pricing or fixed infrastructure? We recommend the architecture that fits your volume, privacy requirements, and budget, because we operate both in production.
• 2-Week Pilot, Pay Only If It Works: Instead of a big-bang AI project, we implement your highest-ROI automation and run it for two weeks with success metrics defined upfront. If the data proves it profitable, you pay for it and we automate the rest of your business; if not, you don't.
• Privacy & Compliance (GDPR): We assess the regulatory side of every use case, what data can be sent to which providers, when self-hosted models are the safer choice, and how to design AI systems that comply with GDPR and the EU AI Act from day one.

How Our AI Consulting Works

1. Process Discovery: We interview your teams and observe how work flows, what gets done manually, what decisions are repetitive, where time and money leak. No AI talk yet, first we understand the business.
2. AI Opportunity Mapping: We match each pain point against what AI can reliably do today (conversational agents, document processing, computer vision, decision support) and discard what is not ready or not worth it.
3. Data & Feasibility Audit: For the surviving use cases we audit your data and systems, is there enough quality data? What integrations are needed? What are the privacy constraints? Each use case gets costs, savings, and a payback estimate.
4. 2-Week Pilot Build: We implement the highest-ROI automation and run it for two weeks with real data and real users, with success metrics agreed upfront, response time, accuracy, hours saved.
5. Measure Against Baseline: We compare the pilot’s results against the baseline measured during discovery. The decision to scale is made with data on the table, not enthusiasm.
6. Automate the Rest: If the pilot proves profitable, you pay for that automation and we move on to the rest of your business with a full roadmap, next use cases, architecture, infrastructure (cloud or self-hosted), and costs. If it doesn't, you pay nothing for it.

AI Technologies We Evaluate and Deploy

From frontier cloud models to self-hosted open-source. We recommend based on production experience with both.

Frequently Asked Questions

How is this different from just hiring you to build an AI agent?

If you already know exactly what you want to automate, you can go straight to our AI agent development service. AI consulting is for when you suspect AI could help but don’t know where to start, we find the use cases, validate them with data, and make sure the first project you invest in is the one with the highest return.

What if the audit concludes AI is not worth it for us?

Then that is exactly what we will tell you, and it happens. Discarding unviable ideas before you spend money on them is a core deliverable of the audit. In most cases, though, the audit also surfaces non-AI automation wins (integrations, custom tooling) that pay for the engagement on their own.

Do we need a lot of data to benefit from AI?

Not necessarily. Modern language models work well without training data for many tasks, answering customers, processing documents, extracting information. Data volume matters for pattern-based prediction and fine-tuning. The data readiness assessment tells you exactly what is possible with what you have today.

Is our data safe? We handle sensitive information.

Data privacy drives the architecture we recommend. For sensitive data we typically propose self-hosted models running on your own infrastructure, so nothing leaves your control, an area where we have deep production experience. Every recommendation includes a GDPR compliance analysis.

How does the 2-week pilot work, and what does it cost?

We analyze your whole business, pick the automation with the highest potential return, and implement it over two weeks on your real operation, with success metrics agreed upfront. You only pay for that automation if the numbers prove it profitable, and then we continue automating the rest of your business, with a fixed scope and price for each next step. The first consultation is free.

Which AI models and providers do you work with?

We work with frontier cloud models (Anthropic Claude, OpenAI GPT, Google Gemini) and self-hosted open-source models (Qwen, Llama, Mistral, LLaVA) on NVIDIA GPU infrastructure. Being vendor-neutral, we benchmark candidates on your real use case and recommend what performs best per euro, sometimes that is a frontier API, sometimes a local model at a fraction of the cost.