Recognition and extraction
OCR makes scanned text accessible, classification suggests a document type and extraction supplies selected fields. We test the approach on your documents, including unusual or lower-quality inputs.
AI that helps process your documents
Reduce manual classification and data entry. We connect AI to document management and workflows, from incoming content to checked information and the next task.
AI-assisted intake
Incoming documents can be provisionally classified and assigned. Uncertain cases go to a person for review, rather than carrying an unnoticed error into the next stage.
Summaries and drafts
AI can prepare a summary, draft minutes or a reply from defined source material. A user checks the content and decides whether to use it.
Data checks and access
We validate output against required fields, reference data and process rules. Access to sources, data retention and the chosen AI service are agreed against the project's security requirements.
Prove value in a pilot
Together we choose a process and success criteria. We measure output quality, corrections and processing time, then decide which steps to put into regular use.
Document → Recognition and OCR → Classification → Data extraction → Validation and exceptions → Routing into workflow. Human review according to risk
Frequently asked questions
How do OCR and AI extraction differ?
OCR recognises text in an image. Extraction identifies fields such as supplier, date or amount. Classification determines the document type. These are different steps that can work together.
What happens if AI gets a document wrong?
The process needs review and correction paths. Uncertain results go to a person, rules check required fields and changes are recorded. A confident-sounding answer is not evidence of correctness.
Will our documents be used to train AI?
That depends on the service, contract and configuration. Before deployment, establish the processor, data location and retention, access controls and permitted use of inputs. The design should answer these questions explicitly.
Does a person have to check every document?
The level of review follows risk, input quality and the consequences of error. Routine steps can be automated; exceptions and important decisions need an owner. Set the rules after testing your documents.
How will we measure the value of automation?
Compare processing time, corrections, completeness and manual interventions before and during the pilot. Include both routine and difficult documents. Benefits should follow measurements, not a general AI promise.
Who can see sensitive documents?
Access is configured by role, group and application. Checks should include previews, exports, service accounts and role changes. Hiding a menu link is not an access control.
What affects implementation cost and timing?
Applications, users, interfaces, data quality and customisation all matter. A proposal should distinguish licences, implementation, migration and support. A useful schedule also accounts for the customer's preparation and participation.