Stage 11 to 2 weeks
AI Opportunity Sprint
Teams who know AI matters but not where to start.
A short, structured discovery that finds the AI opportunities worth pursuing in your business, and the ones that aren't.
Find your AI opportunityDocument intelligence solutions
Document intelligence that turns paperwork into validated data
We build document processing pipelines that read PDFs, scans and photos, pull out the fields you need, check them against your rules and systems, and send only the uncertain ones to a person.
Every extracted field is validated. Low-confidence documents always go to human review.
What usually goes wrong
Businesses still run on documents that arrive in every format imaginable. Someone opens each one, reads it and types the important numbers into another system. It is slow, dull and error-prone, and older OCR templates break whenever a layout changes.
Manual data entry from PDFs and scans
Staff re-type invoice lines, application details or consignment numbers, and every keystroke is a potential mistake.
Layouts that keep changing
Template-based OCR needs a new template for every supplier or form version. The long tail of layouts never gets automated.
Errors discovered too late
A wrong GSTIN, a mismatched quantity or a missing signature is found at month-end reconciliation, not at intake.
Peaks that overwhelm the team
Admission season, month-end closing or a busy shipping week creates backlogs that need temporary staff and overtime.
Where Document Intelligence earns its keep
Invoices
Capture header and line items, validate tax details and totals, and match to purchase orders and goods receipts before posting.
Purchase orders
Read customer POs arriving by email and create sales orders in your ERP, flagging price or quantity discrepancies.
Contracts
Extract parties, dates, renewal terms, payment terms and obligations into a searchable register with clause references.
Applications and KYC forms
Process application forms and supporting IDs, check completeness and consistency, and create records for review.
Marksheets and certificates
Read marksheets from different boards and universities, normalise grades and flag documents needing verification.
Logistics documents
Extract data from e-way bills, LRs, delivery challans and proof-of-delivery photos to update shipments automatically.
What we actually build
Intake channels
Email inboxes, upload portals, mobile capture, WhatsApp and shared folders feeding one processing pipeline.
Classification and splitting
Identify document types, split multi-document PDFs and route each document to the right extraction schema.
Schema-driven extraction
Multimodal AI and OCR that return typed fields and tables according to a schema you approve, with per-field confidence.
Validation rules
Checksums, format checks, totals, master-data lookups and cross-document matching that catch errors at intake.
Human review station
A side-by-side viewer showing the document and extracted fields, highlighting only what needs attention.
System posting and archive
Validated data posted to your ERP, CRM or database, with the original document archived and linked.
Systems we connect to
The usual suspects. If yours has an API or a database, we can almost certainly work with it.
- Intake
- Email (IMAP / Graph), Upload portals, WhatsApp Business API, Mobile capture
- Systems of record
- Tally, Zoho, Odoo, Custom ERPs & school systems
- Validation sources
- Vendor & customer masters, Purchase orders, GSTIN format checks, Internal databases
- Storage
- S3-compatible storage, Google Drive, SharePoint, Document management systems
How it works, step by step
- 01
Capture
Documents arrive from any channel and are converted to a standard format with the original preserved.
- 02
Classify
The system identifies the document type and chooses the matching extraction schema.
- 03
Extract
AI reads text, tables, stamps and handwriting where possible, returning structured fields with confidence scores.
- 04
Validate
Rules and lookups check every field: totals add up, IDs are well-formed, the vendor exists, the PO matches.
- 05
Review or post
Clean documents post automatically if you allow it. Anything uncertain or failing a rule goes to a reviewer, whose corrections improve the pipeline.
Blueprint: supplier invoice processing
Reference design, not a client projectThe scenario: A distributor receives supplier invoices as PDFs and phone photos from many vendors, each with its own layout.
- 1. TriggerInvoice receivedEmail attachment or WhatsApp photo
- 2. AI stepExtract fieldsVendor, GSTIN, date, lines, taxes, total
- 3. Rules & checksValidate & matchTotals, tax maths, vendor master, PO
- 4. Human controlReview exceptionsMismatches shown side by side
- 5. System updatePost to ERPPurchase voucher created, PDF linked
- Trigger
- AI step
- Rules & checks
- Human control
- System update
How we deliver it
Timings are typical for a first release. They depend on scope, how ready your data is and the integrations involved, so we confirm them after discovery.
- 1Week 1
Document sampling
We collect a representative, anonymised sample across layouts and quality levels, define the target schema and record today's handling effort.
- 2Weeks 2 to 3
Extraction benchmark
We measure field-level accuracy on your sample, add validation rules and agree confidence thresholds for automatic processing.
- 3Weeks 3 to 5
Pipeline & review station
We build intake, review and posting, then run in parallel with your current process to compare results.
- 4Ongoing
Extend document types
We add new document types and layouts, and use reviewer corrections to improve accuracy over time.
Safeguards, built in from day one
Security, privacy, testing and human control are designed in from the start, not bolted on after a pilot. We adapt them to your policies and your risk.
Confidence thresholds
You decide the confidence and validation rules required for straight-through processing. Everything else is reviewed.
Sensitive data handling
ID numbers, bank details and student records can be masked in logs, encrypted at rest and processed with providers and regions you approve.
Field-level evaluation
Accuracy is measured per field and per document type on a held-out set, not as one headline number.
Traceable corrections
Every automatic value and every human correction is stored with the document, so you can trace any posted figure back to its source.
What you can expect
Accuracy and automation rates depend on your document mix and quality, so we benchmark on your own samples before committing to targets. Typical aims:
- Less manual typing from documents
- Errors caught at intake instead of at month-end
- Backlogs cleared faster during seasonal peaks
- A searchable, linked archive of processed documents
- Reviewers focused on genuine exceptions
What we measure
Field-level accuracy by document type, Share of documents needing review, Time from receipt to posting, Corrections per 100 documents.
We don't promise savings or accuracy figures up front. We measure them on your data during the pilot.
Where it fits best
- Education. Admission forms, marksheets and certificates.
- Logistics. E-way bills, LRs, challans and PODs.
- ERP & finance. Invoices, POs and expense receipts.
- Legal & procurement. Contracts and tender documents.
Ways to begin
Stage 23 to 5 weeks
Workflow Automation Pilot
One valuable workflow you want to prove before scaling.
A focused pilot that automates a single workflow end to end, running against a measured baseline so the result is a decision, not a demo.
Start an AI pilotStage 36 to 12 weeks
Production AI Build
An AI product or feature you are ready to ship to real users.
A full build from product design to deployment: the AI, the application around it, the integrations and the tooling to run it.
Plan a production buildStage 4Ongoing, monthly
Managed AI Operations
AI systems already in production that need an owner.
Ongoing care for production AI: we watch quality, control costs, handle model changes and keep security reviews current.
Talk about managed AI
Document Intelligence: questions we get asked
What is document intelligence?
Document intelligence (also called intelligent document processing) uses AI to classify business documents, extract the information in them as structured data, validate it and pass it to your systems, replacing manual data entry.
Can it read scanned documents and phone photos?
Yes. Modern multimodal models and OCR handle scans and photos, though accuracy depends on image quality. Poor-quality documents are flagged for review rather than guessed.
How accurate is AI document extraction?
It varies by document type, layout and quality. We benchmark field-level accuracy on your own sample before launch, and validation rules plus human review cover the remaining risk.
Does it work with Indian documents such as GST invoices and e-way bills?
Yes. We define schemas and validation rules for Indian formats (GSTIN structure, HSN codes, tax calculations and e-way bill fields) as part of the build.
Can the extracted data go straight into Tally or our ERP?
Yes, through the ERP's import interfaces or APIs. You choose whether validated documents post automatically or wait for approval.
Drowning in PDFs, scans and forms?
Send us a few anonymised samples. We'll show you what can be extracted, what needs validation and what a pilot would look like. We reply within one business day.
We reply within one business day, and we're happy to sign an NDA first. Prefer email? Write to info@originsphere.in.