Intake
Portal upload, email, Drive, SharePoint, API, and batch intake routes.
Built by Bitlogika
eDocify
AI-powered document operations for OCR, human verification, ERP export, AI Learning, and audit-ready archive workflows.
- B2B SaaS
- Document operations
- Hybrid AI
- Cloud + local OCR
- Azure-ready
- Pilots and scale
Document workflow
From incoming invoice to verified ERP-ready data.
eDocify connects document intake, OCR/AI extraction, human review, approvals, ERP export, and archive evidence in one governed workflow.
OCR / AI
Provider routing across Azure, Mistral, local OCR, rules, and local LLM experiments.
Verification
Verifier workbench, region OCR, confidence reasons, locks, and productivity queues.
ERP + archive
Approval workflow, ERP export, retention, legal hold, audit trail, and evidence packs.
Operational product
Built for finance and document operations teams.
eDocify is not a single OCR screen. It is a product platform for accountants, verifiers, approvers, integration owners, AI learning users, and auditors.
- Role-specific workspaces and access boundaries.
- Field-level review with confidence and source evidence.
- Invoice header and line item verification.
- ERP export validation and repair-oriented workflows.
- Audit-ready archive with retention and legal hold concepts.
AI and OCR stack
Multi-provider, hybrid, and learning-driven.
The platform combines external AI/OCR providers, local OCR routes, deterministic accounting rules, a local LLM R&D path, and Bitlogika's own AI Learning engine.
Cloud AI
Azure Document Intelligence, Azure/OpenAI-style extraction, and Mistral OCR routes.
Local OCR
Tesseract, RapidOCR, and PaddleOCR for private, offline, and cost-controlled routes.
Local LLM R&D
PDF/JPG invoice to RapidOCR or PaddleOCR, OCR text, Ollama Qwen3, and strict JSON schema.
.NET machine learning
Candidate ranking, correction learning, field confidence, and provider-routing signals.
AI Learning engine
Verifier corrections become reusable product knowledge for future extraction quality.
Hybrid governance
Golden datasets, provider bake-offs, release gates, and customer-facing quality metrics.
Proprietary learning layer
Human corrections feed the AI Learning engine.
eDocify captures verified corrections and turns them into learning signals for field extraction rules, candidate ranking, confidence calibration, provider comparison, and tenant-specific behavior.
Golden datasets
Human-approved truth for accuracy gates.
Provider bake-off
Compare accuracy, speed, and cost.
Release gates
Ship AI changes only when quality improves.
Correction learning
Use verifier changes to improve future results.
Pilot scenarios
Designed for measurable B2B pilots.
Accounting firms
Invoice intake, OCR, verification, approval, Rivile/ERP export, and archive evidence.
Metrics: field accuracy, verification time, export success.Enterprise finance teams
AP automation with approval routing, duplicate checks, anomaly detection, and audit trails.
Metrics: cycle time, approval SLA, repair rate.Verification operations
High-volume queues, provider benchmarks, region OCR, quality sampling, and team metrics.
Metrics: documents per hour, correction rate, SLA.Microsoft startup readiness
Why Azure credits matter.
Startup credits would be used for product infrastructure and real pilots: secure environments, OCR/AI workloads, document storage, queue workers, monitoring, secrets, and quality benchmarking.
Build and test
Demo, staging, and pilot environments for finance and document operations customers.
Run AI workloads
Azure Document Intelligence, Mistral comparison, local OCR workers, and hybrid extraction tests.
Measure quality
Golden datasets, field-level accuracy, provider bake-offs, and per-document cost tracking.
Prepare enterprise security
Key Vault, SSO preparation, logs, audit evidence, retention policies, and monitored operations.
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