Automate your document processing with AI
We build custom AI systems that read, understand, and process documents using OCR, NLP, and LLMs. They extract key data and turn messy files into structured output – ready for automation or reporting.
Our Generative AI development expertise
Use cases
AI document processing systems we developed
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1. Invoice and receipt processing
AI can extract and validate data from invoices, receipts, and financial documents – no templates or manual effort required.
What AI can do for you:
- Extract key fields: vendor, amount, tax ID, due date
- Match documents to purchase orders and delivery receipts
- Validate totals and detect duplicates or anomalies
- Feed structured data into accounting or ERP systems
Example use cases:
- Accounts payable automation
- Expense tracking with real-time data capture
- Automated reconciliation and payment prep
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2. Contract review and clause extraction
AI can read documents, extracts clauses, and flags deviations – accelerating legal workflows and reducing risk.
What AI can do for you:
- Identify and extract critical clauses (e.g. liability, NDA, payment terms)
- Flag missing or risky clauses
- Compare against standard templates or prior versions
- Summarize contract obligations in plain language
Example use cases:
- Legal assistant bots for procurement
- Deal desk automation
- Compliance audits across multiple contracts
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3. Email parsing and workflow routing
AI reads incoming emails, pulls out relevant data, and routes it to the right system or team – in real time.
What AI can do for you:
- Classify intent and priority (e.g. support request, invoice, complaint)
- Extract data like customer ID, order numbers, or dates
- Trigger RPA bots or ticket creation
- Generate contextual auto-replies or next steps
Example use cases:
- Support ticket automation
- Email-to-database extraction
- Workflow automation in customer service
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4. ID and KYC document validation
AI extracts data from identity documents and checks them for validity, compliance, and fraud.
What AI can do for you:
- Read passports, driver’s licenses, or business certificates
- Extract names, ID numbers, birthdates, and expiration dates
- Detect expired or tampered documents
- Verify consistency across submitted forms
Example use cases:
- KYC onboarding for banks or fintech
- Identity validation during signup
- Secure employee or partner verification
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5. Forms and survey data extraction
AI captures responses from structured or semi-structured forms and surveys – digitizing handwritten and scanned inputs.
What AI can do for you:
- Read printed or handwritten responses
- Map answers to structured formats (e.g. JSON, CSV)
- Handle varied layouts and field positions
- Flag incomplete or ambiguous entries
Example use cases:
- Customer feedback digitization
- Handling the complaint form
- Insurance claim or application forms
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6. Document summarization (e.g. reports, policies, legal docs)
AI uses LLMs to summarize long documents into clear, concise insights – ready for review, audit, or action.
What AI can do for you:
- Summarize policies, legal docs, contracts, or compliance reports
- Provide bullet-point overviews or plain-language summaries
- Highlight key changes, terms, or risks
- Enable natural language Q&A on document content
Example use cases:
- Legal and policy assistant tool
- Board report digests
- HR policy review tools
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7. Complaint claim automation
AI accelerates complaint resolution by extracting key information, routing messages, and suggesting next actions – all while maintaining compliance.
What AI can do for you:
- Read and understand complaint emails, forms, or chats
- Extract customer details, issue types, and sentiment
- Categorize complaints by urgency or legal risk
- Suggest responses or escalate based on predefined rules
Example use cases:
- Complaint triage and automatic ticket creation
- Escalation routing based on severity or SLA
- Complaint response drafting using past case data
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8. HR document processing (resumes, onboarding docs)
AI helps HR teams process resumes, applications, and onboarding documents.
What AI can do for you:
- Extract skills, roles, and experience from resumes
- Match candidates to job descriptions
- Process onboarding forms (e.g. ID, tax, NDA)
- Flag missing or inconsistent information
Example use cases:
- Resume screening bots
- Automated employee onboarding flows
- Talent database enrichment
They trusted our expertise
Workflow for intelligent document processing
How does AI document processing work?
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Traditional process automation focuses on structured, rule-based tasks
We turn raw documents into structured, usable data — using a fully automated pipeline enhanced by AI.
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Document pre-processing
We clean, convert, and prepare files — removing noise, correcting skew, and optimizing input quality. -
Document classification
AI models classify documents by type (e.g. invoice, contract, ID) to determine the correct processing path. -
Data extraction
We extract text and structured fields using OCR, NLP, and advanced machine learning. -
Data validation
Extracted values are checked for accuracy, consistency, and business logic (reducing errors early). -
Data analysis
NLP and LLMs interpret the content, extract insights, and enable semantic search, summaries, or tagging. -
Integration and human review
Results flow into your systems via APIs — with optional human-in-the-loop review for low-confidence cases.
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Tools and technologies
Our AI tech stack
OCR & document AI
OCR & document AI
NLP & entity extraction
NLP & entity extraction
Large Language Models
Large Language Models
RPA & workflow automation
RPA & workflow automation
Infrastructure & security
Infrastructure & security
We build effective AI AUTOMATION
Key components of AI process automation
Our featured AI document processing projects
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AI Agent
AI assistant for customer service interactions
CLIENT: CREDIT AGRICOLE
- Message understanding: The system extracts key information from incoming messages and generates a summary containing the purpose and emotional tone. It helps eliminate human errors and ensures clear and uniform language
- Intelligent routing: Simple requests are handled automatically for faster resolution, freeing up agents for more complex and personal interactions. More complicated messages are passed to the right teams.
- Generating resources: The system creates customized draft replies and snippets. It can format them into PDFs for sending. It helps improve customer satisfaction scores, and meet service-level agreements.
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AI-based contract analysis
Legal GenAI tool for risk analysis and contract compliance
- Step-by-step contract processing: Upload contracts in formats like DOCX or PDF. The system organizes and categorizes them automatically for easier document management.
- Automated risk and compliance analysis: AI automatically extracts key information, generates a summary, and provides a detailed list of risks and recommendations based on the organization’s knowledge base.
- Legal chatbot assistance: Ask questions about specific sections or compliance issues through an AI chatbot. It provides precise, context-aware answers based on the fine-tuned model and knowledge base.
We build safe, compliant, and ethical AI systems
Security & ethics in AI
Federated learning models
We train AI across distributed datasets without raw data exchange.
Acceptable AI use policies
Our team helps develop and implement policies that govern the use of AI within your organization, ensuring ethical practices.
Ethical AI practices
We adhere to principles of fairness, transparency, and accountability, ensuring that our AI solutions are not only effective but also ethical.
Testimonial
What our clients say
By automating certain customer interactions, bank employees are provided with a prepared “semi-product”, which enables them to dedicate more time to personalizing and empathizing with customer communication, and thus taking even better care of their needs.
Why choose us
AI document processing automation company
Advanced LLM architecture
Industry standards compliance
Domain expertise
Get in touch
Let’s talk
Book 1-on-1 consultation
Grzegorz Motriuk
Head of Sales | Application Development
Our consultant is at your disposal from 9 AM to 5 PM CET working days from Monday to Friday for any additional questions.
FAQ AI document processing
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What is intelligent document processing?
Intelligent document processing (IDP) is the use of AI technologies -such as OCR, NLP, and machine learning – to automatically read, extract, and understand data from documents. It transforms unstructured files (like PDFs or scans) into structured, usable information.
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How is AI document processing different from traditional OCR?
While traditional OCR extracts raw text, AI document processing goes further. It understands the content, classifies document types, extracts key fields, and even handles variations in layout, language, or context – all without relying on templates.
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What are AI document processing services?
AI document processing services help companies automate manual document workflows. This includes extracting data from invoices, contracts, emails, or forms – then integrating that data with business systems such as ERP, CRM, or RPA platforms.
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Do you offer custom AI document processing development?
Yes. At Deviniti we provide AI document processing development tailored to your workflows. We design and build OCR/NLP pipelines, train custom models on your data, and ensure secure deployment — on-premise or in the cloud.
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Do I need to use templates or define layouts for every document?
No. Our models use machine learning and NLP to adapt to varying formats. For common documents like invoices or contracts, we often use pre-trained models that don’t require rigid templates.
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Can I use this solution on-premise for compliance reasons?
Yes. We offer flexible deployment – fully on-premise, hybrid, or private cloud – depending on your security, compliance, and infrastructure needs.