Operations leads
Reduce manual handling across high-volume document queues while keeping teams focused on exceptions.
Automation
Data entry automation
Are you tracking the key terms of your contracts or documents in a spreadsheet?
Using a spreadsheet to track the meta data from your documents means you can only track the headline terms (parties, dates) and are probably missing out on more nuanced terms. Moreover, manual data entry represents a huge cost for your business in terms of time, lost productivity and mistakes.
Manual data entry is prone to errors and spreadsheets are hard to maintain
TextMine's large language model automates manual data entry with a high accuracy saving you time and errors.
TextMine's approach to data entry automation ensures that your business has an evergreen solution which can work with historical and new documents as well as custom queries.
TextMine automates manual data entry from business-critical documents with Vault.
Vault is a large language model which can transform your contracts and documents into a searchable knowledge base:
Vault's large language model technology can extract:
Explicit terms
Important meta data and fields which are present in the document
Answers to key questions
Which are implied by the document’s content
Vault’s AI powered data extraction can be verified manually for improved accuracy.
Vault is also available as a public API.
Automate manual data entry with TextMine
TextMine allows you to automate any use case which involves manual entering data from a document into a spreadsheet or third party system. Whilst the process can be efficient, it does not scale with the number of documents which need to be reviewed or the number of questions which need to be answered as part of the review process. Finally, manual data entry is not trackable which means that it’s very difficult and time consuming to identify errors. Manual data entry leads to errors, inconsistent data and productivity losses.
Why do organisations prefer manual data entry?
Manual data entry is still the preferred form of document data extraction within a number of organisations because the costs are not fully understood and OCR technology has been the default technology for document data extraction. However, thanks to fine-tuned large language models like Vault, the benefits of AI powered document data extraction far outweigh the costs of manual data entry.
What does manual data entry typically look like?
TextMine can automate the process of reviewing documents, trying to locate the piece of information and collating it into a database. Moreover, the process is evergreen meaning that new questions and data points can be tracked retrospectively.
Manual Process
Receive Documents
Read and understand documents
Key in Data
Check Data
What does AI powered data entry look like with TextMine?
Personas and use cases
Automate document-heavy processes with human review where it matters
Automation only works when teams can trust what happened to each document, field, and review decision. TextMine helps process owners standardize intake, extraction, routing, approvals, and downstream updates across repeatable document workflows.
Process owners
Define the steps, checks, and decision points that turn documents into reliable operational outputs.
Review teams
Resolve uncertain fields, escalations, and approvals with the underlying source evidence close at hand.
Common automation workflows
Intake triage
Classify incoming documents, identify missing inputs, and start the right process automatically.
Extraction and validation
Turn documents into fields, validate against rules, and flag uncertain values for review.
Approval routing
Send cases to the right reviewer, team, or approval path based on document content and business rules.
Downstream updates
Push reviewed results into operational systems, reports, or records once required checks are complete.
Answer critical questions about your documents with TextMine!
Effortlessly organise and categorise your documents for seamless document management.
