Document intelligence software transforms your documents, emails, and PDFs into summaries and structured data that you can use.
Document intelligence employs artificial intelligence to handle unstructured documents, emails, contracts, and PDFs, turning them into structured, usable data like summaries, extracted fields, classifications, and identified entities. When applied effectively, it automates tasks that would otherwise need extensive manual reading and data entry, establishing a reliable process for your systems.
Most business information is not kept in tables. It appears in PDFs, emails, contracts, call transcripts, scanned forms, and chat logs, and such content is hard for systems built to read tables to process. Document intelligence solves this issue. We transform unstructured content into concise summaries and organised data usable by other systems. For a fuller explanation of unstructured data and its typical locations, refer to our guide to unstructured data guide to unstructured data.
This feature targets teams that handle large volumes of documents. It helps with reviewing contract terms in PDF files, triaging support tickets, or preparing for meetings when there is insufficient time to read full reports. The pipeline automatically reads and classifies these documents. It extracts relevant facts so staff members need not read and retype the information manually.
Our projects rely on trustworthy data. We start each project by confirming the data is reliable. If the extraction process uses inaccurate information, it will swiftly generate results that look correct but are actually false. We employ the same governed data core for this process as we do for all our other services. This guarantees that the final output stays accurate when verified.
We apply classification, extraction, and normalisation to large volumes of documents, allowing staff to avoid manually entering figures into spreadsheets.
Long documents condensed into the handful of sentences someone actually needs to make a decision.
Natural language processing and machine learning detect individuals, dates, monetary values, topics, and connections within large datasets.
We validate, version, and track each dataset. This ensures we can identify the source of any figure when asked.
Smarter Services is a facilities management company that oversees more than 300 sites. Their team previously devoted one and a half days each week to logging into seven different systems to manually combine data into a report. The company automated this consolidation process. This change saved the team 1.5 days of administrative work each week, enabling them to focus on other tasks.
Read the Smarter Services case studyWe examine your documents, inboxes, and systems to locate unstructured content that holds useful information. We also identify the specific areas where processes are slow or work is being repeated.
We gather content from documents, messages, and systems. We then clean and standardise the formats to make them functional.
NLP, entity recognition, and embedding models organise, extract, and convert information into schemas that your systems can process.
We assign metadata, relationships, and confidence scores to each dataset. We verify these datasets for quality and completeness before they are released.
Pipelines operate continuously as new content arrives. They contain governance features that guarantee each dataset stays accurate and can be traced to its source.
Document intelligence applies artificial intelligence to handle unstructured documents, emails, contracts, and PDFs, turning them into structured, usable data like summaries, extracted fields, classifications, and identified entities. It automates the manual tasks of reading and retyping, and offers a reliable process for your systems.
We handle text, PDFs, images, audio transcripts, emails, chat logs, and other materials that are not pre-formatted in a particular way.
Organising your data boosts model accuracy and cuts training time. This arrangement also makes insights available to multiple teams rather than being confined to a single document.
Yes. Each pipeline contains versioning, lineage tracking, and compliance controls. This guarantees the output is prepared for audits.
Most clients obtain usable, structured datasets within 2 to 4 weeks after the project starts.
We design pipelines that automatically update datasets when new content arrives. This is a continuous process instead of a single cleaning task.
Extraction only justifies its use if the output is accurate enough to act upon. Talk to us about the documents and data sitting untouched in your business, and we'll tell you plainly what's worth structuring first.
Tell us where your data is today and what you want AI to do. We'll come back with a straight answer on what your foundation needs and where the quickest real win is.
Talk to us