Document AI & OCR Services
- Smart Automation
- Security Focus
- Tailored Engineering
Use optical character recognition and document AI to extract, classify, and validate information from scans, PDFs, forms, and images. We build processing workflows that reduce manual data entry and connect structured outputs with your existing systems.
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Top 1% of global
Software Service providers -
ISO 27001 certification
by Bureau Veritas
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GDPR-Compliant processes
for responsible data protection -
AWS trusted infrastructure
for scalable solutions -
Bureau Veritas —
an independent global leader in testing, inspection, and certification.
Why Structured Document AI Processing Matters for Businesses
Documents rarely arrive in a consistent form. They come in different formats, move between disconnected systems, and often need manual entry more than once. Document AI turns scattered inputs into structured information your teams can validate, route, and act on.
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Tell us about your document workflows, and we'll help you find the right approach
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Reduce repetitive data entry
Document AI can capture key fields and validate them before they reach your downstream systems, so there’s less copy-and-paste and fewer corrections to make later.
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Improve data quality
Format checks, reference lookups, and confidence thresholds flag incomplete or inconsistent values early before they reach other applications.
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Make information easier to use
Structured records are easier to search and organize. You can pass them straight to dashboards or operational workflows, shortening the path from document intake to review.
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Plan around volume and cost
Rather than forcing everything through one fixed setup, choose the models and infrastructure that match your document volume, latency, privacy, and budget.
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Support controlled processing
When needed, the pipeline can include role-based access, audit logging, and environment separation to meet your internal security and governance requirements.
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Connect different intake channels
Scans, mobile photos, PDFs, and digital forms can all feed into one shared pipeline, with validation and routing tuned to each source.
Our AI Document Processing Services
We help turn different document types and formats into connected processing workflows. Support can cover the full path from discovery to deployment or focus on the modules your existing system still needs. Whether you need to combine specific modules or rely on us to deliver the complete solution, Beetroot has got you covered.
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Discovery & Assessment
We audit your sources, formats, volumes, SLAs, access rules, and downstream systems, then flag the main risks. You get a phased roadmap showing where AI for document processing is likely to add value, where simpler rules or RPA may be enough, and whether support from our data engineering consultancy is needed.
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Recognition & Layout Parsing
Our OCR services help your team clean and prepare documents by correcting skew, de-noising images, and segmenting pages. We detect languages and read handwriting where feasible. Layout models identify headers, sections, tables, and signatures, leading to higher read rates and fewer manual fixes for better extraction.
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Classification & Routing
Classifiers can label documents by type, language, or sensitivity and select the relevant template or extraction strategy. SLA-aware queues route low-confidence and exceptional cases to the right reviewers, reducing manual sorting and helping teams manage volume spikes.
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Extraction & Validation
Turn documents into structured, usable data with fewer manual checks using document extraction AI. We combine rules and ML to extract key fields, validate them against master data or APIs, and route low-confidence cases for human review.
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Integration & Monitoring
We integrate document-processing pipelines with CRMs, ERPs, EHRs, data lakes, and custom applications through APIs, webhooks, or queues. Depending on the scope, the solution can include SSO, logging, environment separation, and monitoring, with broader custom software development support where the workflow extends beyond document processing.
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Redaction & Privacy Controls
Depending on the use case, redaction workflows can detect sensitive personal, health, or payment data in text and images and apply masking or other agreed controls. Access logs and review queues support accountability and safer information sharing.
See how these services could fit your document workflows
Flexible Cooperation Models
Choose how you work with us. Each model offers flexibility, people‑first collaboration, and clear accountability, without locking you into proprietary platforms.
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Dedicated Development Teams
Long-term cooperationAdd a stable OCR and Doc AI team to your workflows. Scale the team as your needs change while preserving context through shared documentation and working practices. You retain control of priorities, systems, and product knowledge.
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Project Development
Milestone deliveryWork with us for a defined scope, whether that’s invoice capture at scale, claims triage, KYC processing, or migration from a legacy parser. We plan, build, and validate the solution against your requirements, with clear reporting and handover throughout the project.
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Team Workshops
Advanced skill-buildingChoose a focused workshop when your team needs shared understanding before making technical or investment decisions. Sessions can be held online or on-site and shaped around your document workflows, data, and implementation goals.
Choose a cooperation model that fits your team and goals
Example Technologies and Tools We Use
We follow a technology-agnostic approach and choose tools with your context in mind, from document types and security requirements to the systems you already use. Components remain modular, so the solution can evolve without tying your workflows to one proprietary platform.
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OCR and document capture
- Tesseract
- Google Cloud Vision API
- Amazon Textract
- Azure AI Document Intelligence
- PaddleOCR
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Layout and table extraction
- LayoutLMv3
- Table Transformer
- pdfplumber
- Camelot
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Classification, NLP, and redaction
- Hugging Face Transformers
- spaCy
- Microsoft Presidio
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APIs and pipeline orchestration
- astAPI
- Apache Airflow
- Prefect
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Deployment and infrastructure
- Docker
- Kubernetes
- AWS
- Google Cloud
- Microsoft Azure
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MLOps and monitoring
- MLflow
- Weights & Biases
- Evidently AI
- Prometheus, Grafana
OCR AI vs. Document AI. What’s the difference?
Understanding where each approach fits helps you invest wisely, as they solve different parts of the problem. OCR AI focuses on turning scanned images and PDFs into machine-readable text. Document AI builds on that foundation, interpreting meaning and structure so the text becomes usable in automated workflows.
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OCR AI
- Converts scanned images and PDFs into machine-readable text, often with confidence scores and location data. It works well for digitizing archives and making document content searchable.
- Can account for rotated pages, image noise, variable fonts, and multiple languages, depending on the OCR engine and source quality. The setup can be tuned around speed, accuracy, volume, and cost.
- Works best in workflows where humans or simple scripts interpret the results downstream.
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Document AI
- Document AI systems can parse forms and tables, extract entities and relationships, and validate values against business rules or external data.
- Classifiers can identify document types and languages, route documents to the appropriate extraction flow, and flag exceptions for review.
- Supports automated workflows in finance, healthcare, insurance, and logistics where structured extraction, traceability, and controlled review matter.
Meet Specialists for Your Document AI Project
Depending on your needs, Beetroot can bring together OCR, NLP, data engineering, QA, and UI/UX specialists with relevant document-processing experience. They can support recognition, parsing, classification, validation, and human-in-the-loop workflows through a dedicated team or project-based setup. We can share relevant profiles after we clarify your requirements.
Why Choose Beetroot for Document AI
Beetroot combines document AI engineering with human review where it adds value. Our teams take a practical, risk-aware approach, with clear roadmaps, measurable checkpoints, and steady collaboration throughout the project.
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Strategy-to-Production Support
We support the path from discovery and architecture through data assessment, engineering, QA, and rollout. Our broader AI/ML development services also connect document processing with a wider AI system, while documentation and product ownership remain within your organization.
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Flexible Collaboration Models
Engage us for delivery — long-term or project-based — through a dedicated team or team extension. Or future-proof your own team through custom training in emerging technologies. Either way, knowledge stays with your organization and the engagement can scale with the same tech partner.
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Security and Governance at Every Stage
Security and governance are considered throughout development. Depending on the scope, this may include least-privilege access, environment separation, encryption, SSO, and audit logging, with data flows, retention, and access rules reviewed against your policies and compliance requirements.
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Technology-Agnostic Approach
We select engines, frameworks, and cloud services based on latency, privacy, and cost rather than proprietary lock-in. Modular interfaces and clear technical boundaries make it easier to replace or update components as requirements change.
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Efficient by Design, Predictable to Run
We right-size infrastructure, favor efficient models, and design accessible review tools, so the solution stays reasonable for your team to run and operate, and scales as your needs grow.
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Cross-Domain Experience
Beetroot teams have supported software and data projects across finance, healthcare, climate, education, retail, and other domains. We adapt the delivery approach to the workflows, constraints, and stakeholder needs of each project.
Featured Cases
A fraction of our projects that show how Beetroot teams have built data-intensive platforms, structured complex information, and replaced fragmented manual workflows across industries.
Industries We Support
Structured documentation AI flows support teams across domains. We adapt methods to your sector’s rules, formats, and operational realities.
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HealthTech
Reduce admin time and speed turnaround. Document AI turns referrals, lab results, and forms into structured records that post to clinical systems with audit trails intact. This cuts rekeying, shortens turnaround, and supports PHI controls, freeing personnel to spend more time with patients and less on manual paperwork.
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InsurTech
Shorten claim cycles and reduce claims leakage linked to incomplete or inconsistent data with automated capture and routing. Get more complete cases to the right queue while exceptions surface early. Consistent data supports better reserving and clearer customer updates, which can mean fewer rework loops, steadier SLAs, and lower handling costs.
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FinTech
Accuracy and compliance are critical in financial operations. Document AI captures and validates data from statements, receipts, and KYC packs, feeding it directly into core systems. This makes audits easier, speeds up reconciliation, and supports internal KYC and AML controls and review.
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Public Sector
Leverage document AI to turn applications, permits, and case files into searchable records with clear status histories. Improve end-to-end decision tracking, share updates more consistently across teams, and respond to citizens faster. At the same time, agencies can manage retention and disclosure requirements more consistently.
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E-Commerce & Retail
Trust and efficiency depend on consistent catalogs, pricing, and support. Document AI standardizes vendor documents and customer messages so product data and tickets are easier to keep current and accurate. This can reduce listing-related returns, speed up ticket resolution, and strengthen the records used in disputes.
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Manufacturing & Supply Chain
Efficient handoffs keep operations moving smoothly from supplier to warehouse. Document AI captures purchase orders, packing lists, and certificates, feeding verified data into core systems. This reduces mismatches, accelerates goods receipt, improves traceability, and makes audits easier.
Client Testimonials
See what other clients value in our collaboration. While many engagements remain under NDA, the feedback we can share spans QA automation, design, software development, data pipelines, and AI initiatives.
Custom AI & Data Workshops
Targeted upskilling can help your team use new tools more effectively and retain more knowledge internally. Our hands-on sessions are designed around your repositories and roadmap, giving your team practical skills they can apply to current work. For teams exploring wider AI use cases, workshops can also be combined with generative AI consulting.
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Key benefits of our custom workshops:
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Build more capability in-house
Building internal capability can reduce dependence on external support and help your team get more value from existing tools and platforms. -
Retain knowledge and avoid disruption
Sharing system knowledge across the team can make transitions smoother. Documented practices and pairing also reduce dependence on a single expert. -
Make new tech usable
Access to new tools is only useful when the team knows how to adapt them to real work. Focused upskilling helps turn emerging technology into practical workflows rather than leaving it underused.
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Discuss Your Document AI Project
Tell us about your document types, volumes, latency targets, and existing systems. Our experts will get back to you shortly to discuss the best approach, timelines, and team composition to support your goals.
FAQs
These FAQs cover the practical points teams usually consider before introducing OCR or Document AI into their workflows.
