AI document analysis
Document analysis means using AI models to find, extract, compare and summarise the information you need from long documents such as contracts, tenders, policies and reports. Corrplus builds systems that read your documents, return the result as structured data and show which page every answer came from, leaving the final call to the person who knows the document.
Book a free callSymptoms
- Specialists spend much of their time reading the same kinds of documents end to end.
- End dates, penalty clauses and renewal terms are copied into a spreadsheet by hand.
- Answering a simple question means digging through old contracts folder by folder.
- Reviewing a tender or specification eats most of the time you have to bid.
- A non-standard clause is noticed only when it causes a problem.
What waiting costs
A missed clause, a renewal date noticed too late or a bid that misses its deadline costs money directly. As document volume grows, more reading hours alone cannot keep that risk in check.
Our approach
Define document types and questions
With your specialists we write down which fields to extract from which documents and which questions the system must answer.
Read and structure
Scans are converted to text, language models extract the fields and write them to a table with page references.
Compare and flag
Clauses are compared with your standard wording or checklist, and deviations are flagged with a reason.
A searchable archive
Where needed, documents become searchable with RAG; your team asks in plain language and answers come with the source paragraph.
What to measure
- Review time per document
- Share of extractions corrected by hand
- Missed deadlines and renewals
- Time to find a fact in the archive
Our own products
We use the tools and checklists from client projects on our own products too.
All products →Which documents suit this approach?
The best candidates arrive in volume, look alike and always get searched for the same information. Supply and lease contracts, public tenders, insurance policies, technical specifications, audit reports and job applications are typical. Construction and engineering firms often need faster tender and specification review; finance and insurance teams compare policies and contracts.
AI does not replace the specialist here. It turns the hundred pages they would have to read into the five clauses they need to look at. Each flag carries its location in the document, so the specialist can check it in seconds.
Which method answers which question?
| Method | What it does | When it fits | Limit |
|---|---|---|---|
| Keyword search | Finds an exact word | You know the exact phrase | Misses the same meaning in other words |
| Field extraction (LLM) | Pulls dates, amounts, parties, clauses | The same fields matter in every document | The field list must be defined up front |
| Clause comparison | Compares text with your standard | Contract and specification review | You need a standard to compare against |
| RAG assistant | Answers plain-language questions over the archive | Questions are not known in advance | Answer quality depends on document quality |
Most projects build the first two together. If your team needs to ask open questions of the archive, a RAG enterprise knowledge assistant is added as a third step.
How we start
We first pick a small sample of your own documents and mark the correct answers with your specialist. That sample is the only honest way to measure how well a model works on your documents. If the result holds up, we build the document flow through LLM integration and connect incoming documents to the right people with workflow automation.
If documents contain personal data, such as job applications or contracts with individuals, which fields reach a model and where data is stored are settled during design. We use the same approach in our own product, Promptor, when feeding website content to its AI assistant.
AI document analysis: where to start in your business
Tell us where you are in a free first call; we will say plainly where it makes sense to start.
Related services and use cases
Frequently asked questions
Can AI review a contract like a lawyer?
No, and we do not build it to. The model reads, extracts fields and flags clauses that deviate from your standard. Legal judgement and the final decision stay with your lawyer or specialist; the system shortens their reading time.
Can it read scanned and handwritten documents?
Scanned printed documents usually read well. Error rates rise with handwriting and poor scans; those fields are marked low-confidence and go to a person for confirmation.
What if the model makes something up?
Every extraction is tied to a page and paragraph, so it can be checked. When asked for information that is not in the document, the system is set up to say so. For important fields we test accuracy on a sample of your own documents.
Do our confidential documents leave our control?
You decide where documents are processed. Cloud models can run under enterprise terms with no data retention; for stricter needs, open models run on your own servers. We assess GDPR and Türkiye's data protection law, KVKK, together with your legal counsel.
Does it handle documents in several languages?
Yes. Current large language models read English, Turkish, German and other common business languages, and can compare a Turkish contract with an English template. We still test on your own documents before committing to scope.
Let’s talk about your transformation
Tell us which work repeats every week. We will tell you honestly whether it is worth automating.
How we start
- A free first callWe pin down the problem and the goal together.
- A 2-week discovery sprintWe look at the data, the process and the tools, and decide where to start.
- A written proposalScope, architecture and timeline, in writing.