AI and business automation
We build AI capabilities that work inside your organisation: assistants that know your documents and systems, agents that carry out defined tasks, and automation that removes manual steps. Each is integrated with the access controls and records you already govern.
Discuss your situation
Describe the systems involved and what you want to change. An engineer replies within one business day.
Scope of the service
Internal AI assistants
Assistants grounded in your policies, contracts and operational data, answering with sources and respecting the permissions each employee already has.
Autonomous agents
Agents that complete defined tasks across systems, such as preparing documents, triaging requests or reconciling records, with human approval where the risk requires it.
Document processing
Extraction, classification and validation of invoices, contracts, forms and correspondence, feeding structured data into your systems.
Company knowledge search and customer-service automation
Search across document stores, wikis and tickets for employees, and assisted or automated responses for customer service, with escalation paths.
How clients usually start
Use-case assessment and pilot
Six to ten weeks to select a use case with measurable value, build a pilot on your data and evaluate quality, cost and risk.
Production assistant or agent
Hardened deployment with access controls, audit logging, evaluation suites and integration with the source systems.
Automation programme
A portfolio of document-processing and workflow automations delivered in priority order, each with its own business case.
What you can expect from the engagement
- 01
Inside your environment
Models and data are accessed through your cloud tenant or EU-hosted services according to your requirements. Data handling is documented for your governance teams.
- 02
Measured quality
Evaluation sets built with your subject-matter experts define what a correct answer is before release, and are re-run whenever models or prompts change.
- 03
Adoption planned in
Training, guidance on appropriate use and feedback channels are part of delivery, so assistants are used well and improve over time.
Technology we work with in this area
Platform names are used descriptively. We select technology to fit your existing environment and the people who will maintain it.
Frequently asked
Will our data be used to train models?
No. We use enterprise model services and configurations under which prompts and documents are not used for training, and we document those terms for your review.
How do you keep an assistant from exposing information an employee should not see?
Access is enforced at retrieval time using the permissions of the signed-in employee, not a shared service account. The assistant can only cite what that person could already open.
What about the EU AI Act?
Most internal assistants and automations are limited-risk uses, but deployer duties such as transparency, human oversight and record keeping still apply. We document the classification and the controls with you.
How do you measure whether it works?
With an evaluation set agreed before build: representative questions or documents and what a correct outcome is. We report accuracy, coverage and cost per task, and track them after release.
Related reading
- AI and automation
Running internal AI assistants inside your own tenant
What it takes to deploy an assistant that answers from company documents and systems while respecting existing permissions, and what the EU AI Act asks of organisations that deploy one.
- Engineering
Enterprise integration patterns for medium-sized businesses
Which integration approaches suit organisations with a dozen core systems rather than a thousand, how to choose between them, and how to keep the result operable.
AI and business automation: tell us what you want to change.
Describe your environment and the outcome you need. An engineer, not a sales team, reads every request and replies within one business day.