Trusted by teams turning documents into production data
Nanonets' pay-per-block pricing makes extraction costs impossible to forecast at scale. Sensible charges per document. One number, regardless of page count or field complexity.
Per-document pricing
Sensible charges by document extracted; Nanonets' pay-per-block model means costs vary by workflow complexity and are harder to budget at scale
Full-service option
Sensible's team builds and maintains your extraction configs end-to-end; Nanonets offers no equivalent managed service. If your team needs configs built or maintained, you do it yourself.
No training cycle before going live
Nanonets requires model training with sample documents before reaching full accuracy; Sensible's hybrid extraction and 150+ pre-built configs work on day one
Validated output
Schema enforcement catches extraction errors before they reach downstream systems; Nanonets returns structured output without field-level validation
Handles complex document types
Nanonets struggles with messy, handwritten, or highly variable documents; Sensible maintains accuracy on complex layouts with deterministic rules
A Sensible solutions expert will be in touch within one business day.
Trusted by teams turning documents into production data
Pay-per-block pricing ties your extraction bill to workflow complexity. When your document mix changes, costs change with it. Not in a way you can forecast. Sensible charges per document with published pricing tiers, combines hybrid LLM extraction with deterministic validation rules, and offers a full-service option for teams that want configurations built and maintained end-to-end.
Nanonets
Why it matters
Accuracy approach
Hybrid LLM + configurable layout rules
Pure ML models
Hybrid approach leads to higher precision and flexibility
Transparency & Customization
Clear extraction logic with human-readable rules
“Black-box” AI predictions are harder to audit
Easier to rectify errors if they emerge
Edge case handling
Handles 1,000+ page docs, multi-column layouts, recurring tables, nested sections
Struggles with very long or irregular docs
Essential for documents that are higher in complexity
Services & support
Full-service option — setup, integration, and ongoing operations handled
Primarily self-serve, very limited hands-on support
Faster rollout and ability to fully outsource all doc extraction initiatives
Time to value
Go live in days
Requires training cycles and feedback loops
Faster ROI and earlier automation wins
Document coverage
Broad coverage — insurance, banking, real estate, healthcare, utilities, and more
Broad but skewed toward generic forms and simpler forms (e.g., invoices)
Ensures future-proof coverage as use cases expand in variety and complexity
Pricing flexibility
Usage-based, transparent pricing with enterprise options
Subscription tiers; less flexible for scaling up/down
Predictable costs that scale with document volume
All comparisons
Sensible vs Nanonets
Currently viewing
Sensible vs Ocrolus
Financial-services specialist with human-in-the-loop validation
→
Sensible vs Docparser
Zonal OCR with manual extraction zones per layout
→
Sensible vs Docsumo
Pure-AI extraction with an accuracy ceiling on complex docs
→
Sensible vs Parseur
Email-parser built for non-technical teams
→
Sensible vs Extend
AI-only platform without deterministic guardrails
→
Sensible vs Reducto
Vision-language model parsing without configurable rules
→
Sensible vs Hyperscience
Enterprise platform with $50K+ annual minimums
→
Sensible vs Rossum
Invoice & AP specialist with proprietary AI
→
Sensible vs Abbyy
Low-code enterprise IDP requiring consulting engagements
→
Sensible vs Textract
AWS OCR primitive — validation and configs are DIY
→
Sensible vs Kofax
Extraction inside an enterprise workflow orchestration platform
→
Extract from any document type with hybrid AI plus deterministic rules. Validated, traced, and delivered through a production-grade API.