Multi-engine AI OCR on GPT-4 Vision, Document AI, Form Recognizer, and Textract — extracted, validated, and pushed into Odoo / SAP / NetSuite with full audit trail.
95%+ accuracy on invoices, three-way match, PII-safe, compliance-aware (GDPR / HIPAA / DPDP). Real-time or batch.
From invoices to KYC — production-grade pipelines, not Jupyter notebooks.
Extract every line item, tax breakdown, GSTIN/VAT, and total from PDF or scanned invoices — three-way match against PO and goods receipt, post to ERP.
AI reads contracts, extracts key clauses, flags risky terms, compares against your standard playbook, and surfaces only what needs lawyer review.
Aadhaar, PAN, passport, driving licence, utility bill — extract structured fields, verify authenticity hints, push to KYC system with audit trail.
Hand-written or printed forms (loan applications, insurance claims, healthcare intake) — extracted, validated, routed into your system.
Turn 1,000+ PDFs / contracts / SOPs / manuals into a searchable AI assistant — chat, ask questions, get cited answers from your private corpus.
Bulk-process historical documents (5K–500K) into structured data — invoices, statements, reports — to backfill your warehouse or analytics platform.
Real-world documents arrive as scanned PDFs, photos, faxes, email attachments, Excel exports — we normalise the input chaos before extraction.
GDPR / HIPAA / DPDP-aware pipelines — PII redaction, residency-aware processing, audit logs, retention policies, optional on-prem deployment.
One document type (e.g., invoices) end-to-end in 3 weeks. Validate accuracy and savings before scaling.
Multi-document-type pipeline with full compliance, reviewer UI, exception handling, ERP/CRM integration, batch + real-time.
We run the pipeline — accuracy monitoring, model upgrades, exception triage, monthly accuracy report.
Sample 50–200 real documents, run them through 2–3 OCR engines, measure baseline accuracy, identify edge cases. Output: a target accuracy floor in the SOW.
Pick engines per document type, design extraction schema, exception handling rules, ERP/CRM mapping, reviewer UI scope.
Pipeline built — input adapters (email/scanner/upload), OCR + LLM normalisation, validation, ERP push, reviewer UI, observability.
Run alongside manual processing. Measure accuracy vs target, time saved per document, exception rate. Tune extraction prompts.
Full cutover with monitoring. Monthly retainer: accuracy monitoring, model upgrades, new document types, accuracy reporting.
Some engines win on invoices, others on contracts, others on handwriting. We route per document type — not lock you into one vendor.
We measure accuracy formally on a labelled set. Promise an accuracy floor. Show monthly accuracy reports. No 'AI does ~80%' hand-waving.
Real input chaos (email, scanner, photo, fax), reviewer UI for exceptions, audit logs, ERP push, retry/replay — not a Jupyter notebook.
PII redaction, region-locked processing, audit logs, retention policies, on-prem option for regulated industries (BFSI, healthcare, legal).
Free / cheap engines on the easy 80%, premium models on the hard 20%. Our pipelines cost a fraction of single-vendor lock-in.
We know Odoo, SAP, NetSuite, Dynamics — extraction lands as a properly posted entry, not a CSV your team has to import.
Typical accuracy after our tuning phase: 95–98% on printed invoices, 92–96% on contracts, 88–94% on handwritten forms. We measure on a labelled set, promise a floor in the SOW, and route low-confidence items to a reviewer queue.
We're multi-engine — GPT-4 Vision and Claude 4 Vision for complex layouts and unstructured docs, Google Document AI / Azure Form Recognizer / AWS Textract for structured docs at scale, Tesseract for cheap bulk pre-processing. We route per document type for best accuracy + cost.
Yes — Azure Form Recognizer, Google Document AI, and GPT-4V handle handwriting reasonably well (88–94% accuracy on typical forms). For high-stakes handwritten content (legal, medical) we add a reviewer step.
Yes. Extracted data lands as a properly posted entry in your ERP — vendor bill, sales order, customer record — not a CSV import. We routinely integrate with Odoo (any version), SAP, NetSuite, Microsoft Dynamics, and custom ERPs.
We deploy on enterprise-grade infrastructure (Azure OpenAI, AWS Bedrock, Vertex AI) where data does NOT train foundation models. PII redaction at ingress, region-locked processing, audit logs, retention policies. For HIPAA/regulated data we can run on-prem with local Llama/Mistral.
Single document type pilot: 3 weeks. Multi-document production pipeline with ERP integration and reviewer UI: 5–7 weeks. Batch backfill of historical documents (10K–500K): typically a 1–2 week sprint after the pipeline is live.
Pilot pipeline: ₹2L–₹6L ($2.5K–$7K) build + per-document cost ₹0.5–₹5 ($0.006–$0.06) depending on engine and complexity. Production pipeline: ₹5L–₹20L ($6K–$25K) build + per-document cost. Managed retainer: ₹40K–₹2L/month ($500–$2.5K).
Yes. Real-time pipelines (5–30 seconds per document) for live workflows (KYC, invoice approval at receipt). Batch pipelines for backfill. We pick the right mode per document type.
Odoo 20 AI now runs on IAP credits at EUR 1 each. See which features use credits, what scanning, enrichment and SMS cost, and a sample monthly budget.
Free 30-minute audit — we'll run your sample documents through 2–3 OCR engines and send accuracy benchmarks + a fixed-price proposal within 48 hours.
