Applied Layer

How we work

Understand first. Build second.

Our process is built in four layers. Each one rests on the one beneath it, so by the time we build anything, we know it’s worth building.

The four steps

  1. Step 01

    Assess

    We study how your business actually runs: its structure, workflows and data.

    We start by listening. We talk to leadership and to the people doing the day-to-day work, look at the tools and documents they use, and review the data you have. The aim is to understand the business as it really operates, not as the org chart describes it.

    What happens

    • Interviews with leaders and frontline staff
    • Walkthroughs of key workflows
    • A review of your systems, documents and data quality

  2. Step 02

    Identify

    We find where AI creates real value, and say so plainly when it doesn’t.

    With a clear picture of the business, we look for the places where AI would make a measurable difference: time saved, errors reduced, better answers for customers. We also point out where a simpler fix (a better spreadsheet, a cleaner process) would do the job. Sometimes the honest answer is that AI isn’t the right tool yet.

    What happens

    • A ranked list of opportunities by value and effort
    • A clear recommendation for the first project
    • Agreed success measures, set before anything is built

  3. Step 03

    Build

    We build the solution with the right mix of closed and open-source models.

    We choose models for the job, not out of loyalty to a vendor. That might be a hosted model such as Claude, GPT or Gemini for complex reasoning, an open-source model such as Llama, Mistral or Qwen for privacy and lower running costs, or both. We build in short cycles and show you working software early, so you can steer.

    What happens

    • Model selection weighed on cost, privacy and performance
    • Short build cycles with regular demos
    • Testing against real examples from your business

  4. Step 04

    Deploy & support

    We put it into production and help your team use it well.

    A tool only helps if people use it. We deploy into your environment, connect it to the systems your team already works in, and run training sessions. After launch we monitor quality, fix issues and adjust as your needs change.

    What happens

    • Production deployment and monitoring
    • Team training and written guides
    • Ongoing support and improvements

Timelines and pricing depends on the scope and are discussed before work begins.

Working together

What we need from you

Not much, but these four things make the difference between a project that lands and one that drifts.

  • A named point of contact

    Someone on your side who can make decisions, answer questions and open doors internally.

  • Time with the people who do the work

    A few hours with the staff who run the process day to day. They know where the real problems are.

  • Access to relevant data and systems

    Sample documents, data exports or test accounts, shared under whatever security terms you require.

  • A clear picture of success

    What would make this worth it for you? We agree on that together before we build anything.

Data security & confidentiality

Your data is treated as confidential from the first conversation.

AI work often touches sensitive information. Here’s how we handle it.

  • NDA and GDPR from day one

    We’re happy to sign an NDA before you share anything sensitive. As a company registered in Estonia, we handle personal data under the GDPR, the EU’s data protection law, and can sign a data processing agreement.

  • Least access needed

    We ask only for the data a task needs, and prefer samples or anonymised data where they’ll do.

  • Your data stays yours

    We don’t use your data to train models for anyone else, and we don’t reuse it across clients.

  • Private deployment options

    Where data must not leave your environment, we can run open-source models on your own infrastructure.

  • Careful use of hosted models

    When we use hosted AI providers, we choose business plans whose terms say your data isn’t used for training, and we explain those terms to you.

  • Clean handover

    At the end of an engagement we return or delete your data as agreed, and hand over all credentials.

Start with a conversation.

The first step is a free consultation. We’ll ask how your business works, listen, and tell you honestly whether we think AI can help.

Book a free consultation Email hello@appliedlayer.io