Trusted by teams turning documents into production data
Why choose Sensible over Hyperscience? Skip the $50K minimums, weeks of platform setup, and proprietary ML training cycles. Deploy in days with transparent pricing.
10x faster implementation
Go live in days, not weeks or months, with just 1 sample document needed
Developer-friendly approach
Simple APIs and transparent configs vs. complex enterprise platform infrastructure
Predictable, transparent pricing
Clear costs from day one vs. $50K+ starting price with complex volume-based licensing
Full control and transparency
Readable, auditable rules you can customize vs. proprietary black-box ML models
No vendor lock-in
Flexible, API-first design that integrates anywhere vs. enterprise platform dependency
See how Sensible handles your hardest documents.
Trusted by teams turning documents into production data
While Hyperscience is an enterprise AI platform built for large-scale operations with complex infrastructure, Sensible offers a nimble, developer-friendly alternative that delivers production-ready accuracy in days instead of months. Hyperscience's approach requires significant upfront investment (starting at $50K+), lengthy implementations, training samples, and proprietary models that create vendor dependency. Sensible combines the flexibility of modern LLMs with transparent, configurable extraction rules — giving you control, predictability, and the ability to customize without becoming an ML expert. Whether you're a startup or enterprise, Sensible delivers faster time-to-value with clearer pricing and no platform lock-in.
Hyperscience
Why it matters
Time to production
Deploy in days with pre-built configs and instant API access
Multi-week implementations requiring platform setup, workflow configuration, and model training
Start extracting data and seeing ROI 10x faster without lengthy setup, configuration, or model training cycles
Starting cost
Pay-as-you-go with transparent per-document pricing
$50K+ annual minimum for Essentials package, plus implementation fees
Accessible for startups and mid-market companies without enterprise-only budget requirements
Training requirements
Just 1 sample needed — LLMs + layout rules start working immediately
Requires 400+ training samples for semi-structured documents to build ML models
Start immediately with a single example document instead of collecting hundreds of samples for model training
Approach & transparency
Configurable hybrid: LLMs for flexibility + layout rules for precision
Proprietary ML models (ORCA VLM) with limited visibility into decision-making
Understand exactly how extraction works, debug issues easily, and maintain full control without vendor dependency
Developer experience
Simple REST API with comprehensive docs — integrate in hours
Hypercell platform requiring learning blocks, flows, and low-code interface
Integrate in hours with standard APIs instead of learning a proprietary low-code platform architecture
Configuration approach
Human-readable JSON configs stored in your version control
Visual low-code blocks and flows configured through platform UI
Treat extraction logic as code with version control, testing, and CI/CD integration like any other software
Infrastructure requirements
Cloud-native SaaS — zero infrastructure to deploy or manage
Enterprise platform deployment on AWS, Azure, or GCP with infrastructure management
No platform to manage, deploy, or maintain — just call an API and get results
Maintenance burden
Update configs as documents change — no retraining needed
Continuous model lifecycle management, retraining, and expert-in-the-loop optimization
No ML expertise required for maintenance — update extraction rules yourself without retraining models
Vendor flexibility
Lightweight API integration — switch or supplement easily
Deep platform integration with custom blocks, flows, and model dependencies
Maintain flexibility to switch or supplement solutions without rebuilding your entire document processing infrastructure
Customization control
Direct control over rules, prompts, and extraction logic
Customize within platform's block architecture and model constraints
Customize extraction to your exact needs without platform constraints or waiting for vendor features
Human review workflows
Built-in HITL with configurable confidence thresholds
Sophisticated HITL and expert-in-the-loop for model optimization
Both platforms support human review — Sensible makes it accessible without enterprise platform complexity
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Lending-specialist OCR with human-in-the-loop review
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Pay-per-block pricing that varies with workflow complexity
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Docparser
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Docsumo
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Extend
AI-only platform without deterministic guardrails
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Hyperscience
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Invoice & AP specialist with proprietary AI
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Low-code enterprise IDP requiring consulting engagements
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Skip the platform setup. Get a Sensible demo in 30 minutes.