Applied AI

Built on your data.
Measured in use.

Knowledge search, AI agents and workflow automation on your data and tools, with evaluation, access controls and LLM observability.

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Accuracy targets
agreed up front.

Knowledge search, AI agents and workflow automation, connected to your documents and tools through retrieval and MCP integrations.

Built on your data platform, and on models inside your perimeter where needed.
Solution scope

The application, connected

Business context first.

  1. Your knowledgeDocuments, systems and business context
  2. Retrieval & modelsThe right sources for each request
  3. AI applicationSearch, agents and automation, with MCP tools
  4. Evaluation & controlsAccuracy, access and cost per request
Observed in production with LLM observability

What you take away

  1. 01

    One use case, in front of users

    Search, an agent or an automation built around a real workflow.

  2. 02

    Evidence of quality

    An evaluation suite with accuracy targets agreed up front.

  3. 03

    Controls around your data

    Access boundaries and defences against prompt injection and data leaks.

  4. 04

    Cost you can see

    Per-request cost tracking and budgets, with LLM observability.

Chosen for your requirements and your existing environment.

Built in stages.
Operated 24×7.

The team that builds it runs it, from the first decision through ongoing operation.

  1. 01 / Define

    Agree the outcome.

    Scope, constraints and success measures.

  2. 02 / Build

    Build it as code.

    Infrastructure, data or AI, in working stages.

  3. 03 / Validate

    Prove it on real work.

    Real workflows, real traffic, a rehearsed restore.

  4. 04 / Operate

    Run it 24×7.

    Monitoring, on-call, upgrades and improvement.

Explore our approach ↗

The value,
in practice.

A closer look at a related client engagement.

Education & coaching

AI coaching that remembers.

A coaching network with 25 years of in-person centres across Germany.

Explore the project
Project outcome
A coaching assistant people come back to.
Higher engagement.Users return to an assistant that remembers their goals and progress.
Less coach effort.Summaries, nudges and recommendations replace manual follow-up.
A dependable engine.The coaching engine stays available as daily conversations grow.
Education & coaching · individual engagementView case study

Your next step

Pick one workflow.
Prove it there first.

Forty-five minutes on your workload, environment and constraints. You leave with a proposed first step.