03 — Automate

AI integration and workflow automation services

We add AI where it does a specific job reliably — reading, classifying, summarising, extracting — and automate the repetitive steps around it, inside the tools and products you already use.

Discuss an automation What the work covers

Good candidates for automation

  • Someone re-types the same information into several systems
  • Incoming emails, forms or documents are sorted by hand
  • Reports are rebuilt manually every week or month
  • Your product needs search, summaries or classification
  • Support or operations teams answer the same questions repeatedly
  • You want to test whether AI can handle a task before committing to it

What the work covers

AI features in products

Summaries, classification, extraction, search and assistants built into your application using AI APIs or models.

Workflow automation

Connecting forms, inboxes, spreadsheets, CRMs and databases so routine steps run on their own.

Model implementation

Implementing and, where justified by the data and the task, training machine learning models.

Evaluation and safeguards

Testing AI output against real examples, with fallbacks and human review where mistakes are costly.

How an automation project runs

  1. 01

    Map the task

    We document the current steps, inputs, outputs and where errors would matter most.

  2. 02

    Choose the approach

    Rules, AI, or a mix — chosen by reliability, cost to run and how results will be checked.

  3. 03

    Prototype on real examples

    We test with your actual data before building the full workflow.

  4. 04

    Integrate and monitor

    We connect it to your systems, add logging and hand over how to review and adjust it.

How we work on every project

What you receive

  • A working automation or AI feature in your environment
  • Notes on accuracy observed during testing and known limits
  • Configuration for prompts, rules or models that you can adjust
  • Documentation of data flows, costs to watch and failure handling

What helps us start

  1. 1A description of the task and how it is done today
  2. 2Representative examples of the inputs and expected outputs
  3. 3Access to the tools or systems involved
  4. 4Any data-handling or privacy requirements that apply

Questions about this service

All questions
Is AI the right fit for my problem?

Sometimes. We’ll tell you if a rule-based automation would be more reliable or cheaper to run, and recommend AI only where it does the job well.

What happens when the AI gets something wrong?

We design for it: confidence checks, fallbacks and human review steps where errors would be costly, plus logging so mistakes can be found and corrected.

Will our data be used to train AI models?

That depends on the provider and settings used. We’ll review the options with you and choose a configuration that meets your data-handling requirements.

Web scraping, data extraction and system integrationCollect and prepare the data your automation depends on.Custom software and web developmentBuild the application your AI feature lives in.Cloud infrastructure, migration and managementRun automations reliably in the cloud.

Got a task your team repeats every day? Let’s look at it.

Discuss an automation