Capabilities · Intelligent Document Processing

Turn documents into decisions, automatically.

Intelligent Document Processing fuses OCR, AI algorithms and business domain rules to classify, extract and validate data from any document type — structured, semi-structured or scanned — before handing it to RPA for enterprise posting.

01 — The pillars

Four components, working in concert

We eliminate brittle template dependencies by synthesising advanced optical recognition, generative reasoning, deterministic domain rules and automated execution into a single cognitive pipeline.

Optical Character Recognition (OCR / ICR)High-speed neural character and image recognition capable of digitising skewed, noisy, multi-DPI scans and handwritten notations with pixel-level precision.

Artificial Intelligence AlgorithmsProprietary multimodal AI models and Large Language Models that understand natural-language context, complex tabular hierarchies and document structure — without a fixed template per source.

Business Domain Specific RulesMathematical balance validations, GSTIN / Tax ID verification, line-item PO cross-matching and deterministic guardrails that prevent AI hallucinations in production.

Intelligent Automation & RPASeamless autonomous handoff into downstream systems — transmitting structured data into Oracle, SAP, Salesforce or custom databases using RPA bots, without human re-keying.

No single technology is a silver bullet. Our hybrid approach combines each component's strengths to deliver cost-effective, accurate and flexible document automation.

02 — Document scope

The kinds of documents this handles

A few examples of what we have processed — not a list of limits. The approach generalises to whatever your business receives, regardless of format, department or layout complexity.

Financestructured and semi-structured

Invoices, purchase orders, payment advices, utility bills, credit notes

Identityphotographed and scanned

Aadhaar, PAN, driving licence, passport

Government & statutoryfixed formats, frequent revisions

Government forms, Form 26AS, GSTR documents, e-way bills, tax notices

Insurancelong, clause-heavy

Policies, endorsements, claim forms and related paperwork

Organisation-specificyour formats, your counterparties

Bank statements, vendor and customer ledgers, contracts, dockets

Multi-document filesseveral documents in one

Classified, split and individually extracted by our algorithms combined with LLMs

03 — Selecting the right approach

Not all document AI is the same

While OCR and ICR have evolved gradually, the real advances have come only in recent years. The key to success is choosing a cost-effective, scalable approach that fits your specific needs — which starts with three questions.

What is the nature of the document?

How difficult is it to replace or upgrade the technology?

Have AI hallucination risks been accounted for?

Pure OCR / template-matching

Works only for documents you already know

Classical OCR locks every field to a fixed coordinate on a known template. Add a new vendor, change a form layout, or receive a handwritten annotation and the extraction breaks. Every new document type requires a new template — and a person to build it.

Requires a template per document source
Fails on layout variation and handwriting
Cannot understand natural-language context
Every exception needs manual correction

BOT Mantra Intelligent Document Processing

Generalises to any document, with guardrails

Our hybrid pipeline reads any document — typed, scanned or photographed — then uses AI to understand structure and meaning, and deterministic rules to validate what was extracted before it ever reaches a downstream system.

No template needed per document source
Handles structured, semi-structured and unstructured formats
Business rules prevent AI hallucinations in production
Modular: swap OCR or LLM engine without rebuilding workflows

By combining diverse technology components rather than betting on one, we deliver solutions that improve cost-effectiveness, accuracy and flexibility.

04 — The processing pipeline

Six stages, from scan to system

Every document passes through the same six-stage architecture, ensuring that raw input is transformed into validated, audit-ready structured data before any automated action is triggered.

01Raw Data ExtractionEverything the page contains, before any judgement is applied.

02Data FormattingNormalising what came off the page — denoising, deskewing, orientation correction.

03Data ClassificationDeciding what the document is and splitting multi-file bundles automatically.

04Relevant Data ExtractionPulling only the fields the downstream process needs, via LLMs and layout parsers.

05Domain Rules ValidationChecking the values against your business rules and mathematical constraints.

06Robotic Process AutomationPosting validated records into Oracle, SAP or your core ERP — without human re-keying.

05 — Proven deployments

Where enterprises are using this today

Leading global enterprises use BOT Mantra's IDP platform to replace weeks of manual paperwork with reliable, audit-ready automation.

Invoice Processing — Accounts Payable

Classify, split and extract from multi-document files

Organisations often receive multiple documents stitched together in a single file, making it challenging to classify, separate and extract relevant data efficiently. Our proprietary AI algorithms, combined with LLMs, automate this process — ensuring structured data extraction and seamless integration with downstream workflows.

Automated PO Matching

Extracts and cross-validates invoice line items against purchase orders stored in the ERP.

ICT Allocation

Allocates invoices to sister concerns based on PO details for financial postings.

Workflow Automation

Handles multi-tier approvals and manual human exceptions before final BOT execution.

85% reduction in manual effort

Processing time reduced from 20–25 days to 6–8 days, even for complex invoice batches.

Contract Indexing & Management

Effortless document management with automated indexing

Without proper management, digital contract files become disorganised and difficult to navigate. Document Indexing structures and categorises contracts by assigning keywords and metadata, making retrieval faster and more accurate. Automating this process enhances efficiency, reduces errors and saves valuable time.

LLM-Powered Analysis

Extracts key parties, dates, clauses, obligations and provisions from contract documents.

RPA BOT Automation

Extracted metadata is stored in enterprise systems, enabling automated alerts and instant reference.

Faster Retrieval

Quickly locate renewal dates and indemnity clauses across thousands of contracts in seconds.

Scalability & accuracy

Handles large volumes of contracts without human copy-pasting, at any scale.

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Enterprise AI strategy & implementation
Intelligent Process Automation
Agentic AI & Virtual Agents