Invoices
Templates, fields, rules and approvals shaped around the process.
AI DOCUMENT AUTOMATION
AI Document Automation for Business
Re:Brain() helps automate document creation, checking and processing: moving data from spreadsheets, CRM, email and forms into templates, applying business rules, finding errors and sending the finished result for approval.
We start with a real document and the process behind it.
AI DOCUMENT AUTOMATION
What documents can be automated
Commercial proposals
Templates, fields, rules and approvals shaped around the process.
Contracts and addenda
Templates, fields, rules and approvals shaped around the process.
Reports and presentations
Templates, fields, rules and approvals shaped around the process.
Requests and internal forms
Templates, fields, rules and approvals shaped around the process.
Transport and logistics documents
Templates, fields, rules and approvals shaped around the process.
Instructions and internal templates
Templates, fields, rules and approvals shaped around the process.
What operations can be automated
- Collect data from Excel, Google Sheets, CRM, email, PDF or forms
- Recognize and structure data
- Populate templates
- Apply formulas, rules and validations
- Compare versions
- Detect missing or conflicting fields
- Generate PDF, DOCX and XLSX files
- Manage approvals, statuses and an audit log
- Send documents to Microsoft 365, Google Workspace, CRM, email or internal systems
When AI is needed and when regular automation is enough
Not every step should be handled by a language model. A reliable solution assigns work to code, rule-based logic, AI and people where each is strongest.
Code and rules
Hard rules, exact calculations, formulas, required fields and validations should run in code or rule-based logic.
AI
AI is useful for recognition, classification, unstructured text, finding relevant passages and preparing drafts.
People
Critical documents, exceptions and decisions with business consequences should be reviewed and approved by a person.
How the work happens
01
Discovery and process map
We map data sources, document owners, delays, manual steps and error points.
02
Fields, rules, roles and exceptions
We describe document structure, calculations, conditions, statuses, access and edge cases.
03
Prototype
We test the idea on real anonymized examples instead of production data.
04
Testing and acceptance criteria
We define the expected output, test normal and edge cases, and agree acceptance criteria.
05
Integrations
We connect Excel, Google Sheets, CRM, email, Microsoft 365, Google Workspace, PDFs, databases or APIs.
06
Launch and adoption
We provide documentation, train the team and help fit the workflow into daily work.
Implementation formats
Simple workflow
A sequence of steps with clear inputs, rules and output.
No-code / low-code automation
A fast way to connect data sources, templates, approvals and notifications.
Internal AI tool
A team interface for preparing, checking or routing documents.
Custom MVP
A prototype shaped around your specific logic, document formats and team roles.
Integration into an existing system
Embed the automation into the CRM, Microsoft 365, Google Workspace or another system the team already uses.
DOCUMENTED CASES
What is already documented in published cases
These examples show related scenarios involving data, templates, calculations and reporting documents. We do not add unverified results.
Client reporting automation
An Excel report had to become a branded presentation with charts and conclusions. A tool automated preparation of that document.
View cases →Turnkey commercial proposal
A workflow pulled assets, calculated parameters and prepared the client email from selected products.
View cases →Consolidated CEO reporting
A shared file format, aggregation and an AI summary provided a management view without manually combining every file.
View cases →FAQ
AI document automation FAQ
Yes. Automation can often connect to an existing CRM, ERP or email through APIs, files, spreadsheets or an integration workflow. We first identify what already works and where an automation layer is useful.
Yes, when the required integrations and permissions are available in the specific environment. Workflows may use Outlook, Excel, SharePoint, Google Drive, Gmail, Google Sheets and other supported sources.
Yes. A spreadsheet can provide fields, rows, calculations or statuses that are then moved into a document template or the next workflow step.
Exact calculations and required rules run in code or rule-based logic. Critical documents can also have test scenarios, an audit log and human review.
Yes, when document quality supports recognition. Scans require a separate check of OCR, field structure, language, tables and exceptions using real anonymized examples.
During discovery we agree what data may be sent to AI, where it is stored, who can access it and what must be masked. A prototype can start with anonymized documents.
No. We can start with one document and the current process. During discovery we define fields, rules, roles, exceptions and acceptance criteria.
Show us one frequently repeated document and how it is prepared. We will identify data sources, manual steps, rules and the smallest useful prototype.
Show us one document and how it is prepared
We will identify what can be automated, where AI is useful and which prototype to start with.
Discuss the process