Time saved
Less manual copying and comparison.
AI Engine module · Document agent
Document data ready for the next step.
Reads agreed document types and checks data against company rules. It can also support technical documentation, attachments and protocols.
What the AI does
Identifying type and period
balance sheet · fiscal year 2025 · comparative column 2024
Scan without a text layer: OCR
4 pages · stamp and signature on page 2
Reading tables0 / 42
line items into the balance sheet schema
Checking control totals
assets = equity and liabilities · current assets: PLN 500 difference
Checking period consistency
opening 2025 = closing 2024
Handing over to the analyst
1 discrepancy · original next to the data
Data for the analytical sheet
Counterparty A · balance sheet 2025
closing 2024 = opening 2025
Non-current assets12,480,000
Inventories2,140,500
Short-term receivables4,862,800
Cash1,212,500
Total current assets8,215,300
Total assets20,695,300
Total equity and liabilities20,695,300
Line items add up to PLN 8,215,800, the document says PLN 8,215,300. PLN 500 difference in receivables: there is a stamp over the row.Totals and periods match after the analyst’s correction. Only approved data goes into the sheet.
ApproveCorrectReject
Saved to the analytical sheet
Module demonstration with sample data.
Workflow
How the agent works
A document enters an agreed workflow. The agent extracts information, checks it and prepares the next step for review.
Identifies documents and reads fields.
Checks completeness and consistency.
Sends exceptions to a person for review.
Prepares data for the target system.
The value comes from less manual reading and more consistent checks across the document flow.
New possibilities
Repeatable checks can cover every document in scope, rather than a sample.
Integrations
Possible integrations
Connections establish where documents arrive, which sources verify them and where the approved result goes.
EmailDocument repositoriesERPWorkflow systems
We confirm the scope after reviewing data, permissions and interfaces.
Launch conditions
We agree launch conditions after reviewing the data and integration scope. Together, we define the process, preparation needed and acceptance criteria.
Skills and processes
- Document extraction
- Completeness checks
- Consistency checks
- Exception handling
Getting started
Let’s check readiness to start
You do not need everything ready in advance. Together, we review these areas, identify gaps and agree what to prepare before a pilot.
Document samples. Gather typical files and difficult cases. Identify which data should move into the next step of work.
Validation rules. Describe what makes a document complete and correct. Together, we check which rules are documented and which need clarification.
Workflow and integrations. Agree where files arrive and where results go. We review systems, data formats and required permissions.
Exceptions. Identify who reviews ambiguous cases. Agree a pilot sample and acceptance criteria.
Pricing
What the price depends on
Document types
How many document types and layouts, including scans, the agent has to read, and how many rules it checks the data against.
Flow and systems
Where the files come from and where the result goes, for example email, a document repository, ERP or a case management system.
Data security
Whether documents may go to the cloud or the agent has to run on your servers with a local model.
The first call is free. We quote the price after reviewing the data and integrations, and when the idea first needs testing on your data, we start with a feasibility study.
Let’s talk about the work you want to improve.
Tell us how a process works today. Together, we will explore where AI Engine can help and which module to start with.
Book a callOr write to: hello@wearefuture.ai
