Your Model Thinks "Apple" is a Fruit
When You Need NASDAQ Data
Poor entity recognition isn't just wrong — it's expensive. Missed entities corrupt knowledge graphs. Inconsistent tagging breaks compliance workflows. Context-blind annotation turns financial reports into fruit salad.
Our linguistic experts deliver NER annotation that actually works in production. Multi-stage quality control, domain-specific understanding, and support for over 100 languages.
Poor NER Annotation is Sabotaging Your NLP Models
A missed entity becomes a lost customer insight. Inconsistent tagging corrupts your knowledge graph. Context-blind annotation turns "Apple" into fruit salad when you needed NASDAQ data.
Entity Boundary Errors
Misaligned entity boundaries in complex names. "New York Stock Exchange" becomes "New York" + "Stock Exchange" — breaking your downstream analytics and entity linking.
Inconsistent Labeling
Inter-annotator disagreement rate with crowdsourced labeling. Same entity, different tags across your dataset. Your model learns noise instead of patterns.
Domain Blindness
Critical domain entities missed by generic annotators. Medical codes, financial instruments, legal citations — invisible to workers without expertise.
Your Entity Recognition Needs Precision
Linguistic experts who understand context. Multi-stage quality control. Domain-specific entity models that actually work in production.
Most NER Annotation Fails in Production
Common Problems
- Annotators without linguistic training
- 30-40% inconsistency between reviewers
- Generic workers unfamiliar with your domain
- Errors discovered only in production
- Standard entity types that miss edge cases
- Misaligned boundaries breaking pipelines
Enterprise-Grade Solution
- Linguistic experts with domain training
- Multi-stage validation and QA process
- Industry specialists who know your terminology
- Iterative delivery with feedback loops
- Custom entity taxonomies for your needs
- Pixel-perfect character-level precision
A Process That Delivers Results
Schema Design
Define your exact entity types and edge cases
Expert Annotation
Domain specialists tag with context awareness
Triple Validation
Cross-validation, QA review, consistency checks
Direct Integration
Export to your exact format and pipeline
Integrates With Everything
Your NLP Model is Only
as Good as Your Entities
Missing a single organization name can break compliance workflows. Confusing "Apple" the company with "apple" the fruit corrupts your entire knowledge graph. Bad entity annotation isn't just inaccurate — it's expensive.
Our linguistic experts deliver context-aware NER annotation that actually works in production. Multi-stage quality control. Domain-specific understanding. Support for over 100 languages.
NER Annotation That Actually Ships
No crowdsourced guesswork. Just expert annotators who understand context, domain terminology, and the difference between precision and recall.
Domain-Specific Models
Your industry has unique entities. Gene names, legal citations, financial instruments — we train annotators on your specific taxonomy.
- Custom entity hierarchies (sub-types, relations)
- Industry-specific training materials
- Consistent boundary detection
Context-Aware Tagging
"Washington" the person, place, or team? Our annotators read full documents to disambiguate entities based on context.
- Coreference resolution included
- Alias and variant handling
- Cross-sentence entity tracking
Production-Ready Output
Export in any format: CoNLL, spaCy, JSON, CSV. Direct integration with your ML pipeline. No conversion headaches.
- Character-level offset precision
- Confidence scores per entity
- Relationship annotations available
Stop Training Models on Noisy Data
Free pilot project. See the quality difference in 3-5 days. No commitment until you're convinced.
Stop Settling for 85% Accuracy
While others treat NER as a commodity service, we've built a precision engine that delivers 99.2% first-pass accuracy through domain expertise, not guesswork.
The Expertise Gap
Crowdworkers googling "what is a gene name?"
Generic annotators missing industry nuances
15-20% error rate requiring 3+ QA rounds
PhD linguists + domain experts in your field
Medical doctors annotating clinical notes
99.2% accuracy on first pass—ship immediately
Entity Intelligence That Understands Context
"Dr. Chen administered 5mg of pembrolizumab for NSCLC with PD-L1 expression ≥50% per Protocol NCT02220894"
The False Economy of Cheap Annotation
94% → 99.3% accuracy
6 weeks → 72 hours
67% cost reduction
The Bottom Line
Go Cheap, Pay Twice
- 15-20% errors poison your training data
- 3+ weeks of back-and-forth corrections
- Models that fail in production
- Competitors launch while you debug
Choose Precision, Ship Faster
- 99.2% accuracy from day one
- Production-ready in 72 hours
- Models that outperform competitors
- Launch 3 months ahead of schedule
100% Accuracy Guarantee or Full Refund
Your NER Models Keep Failing Because
Your Training Data Is Wrong
Stop wasting $50K+ fixing bad annotations from crowdworkers.
Get 98% accurate NER data from actual domain experts in 72 hours.
Right Now, You're Dealing With:
Real Experts, Not Freelancers
Medical doctors annotate clinical notes. Financial analysts label SEC filings. Patent attorneys tag IP documents. People who actually understand what they're reading.
Accuracy
Triple-Validation Protocol
AI pre-annotation → Expert review → Senior QA specialist. Every entity verified three times. Inconsistencies caught before they corrupt your model.
Industry Best
72-Hour Guaranteed Delivery
10,000 documents? 72 hours. 100,000? Still 72 hours. Our 500+ expert annotators work in parallel. No delays. No excuses. Ship on schedule.
Volume
From Upload to Production in 4 Days
No lengthy onboarding. No complex setup. Just results.
What 98% Accuracy Actually Means
vs In-House
Manual QA
Improvement
Failures
Test Our Quality Risk-Free
1,000 Free Annotations
Send us your most complex documents—the ones everyone else gets wrong.
We'll annotate 1,000 entities free. Compare against your current provider.
Annotated
Time
Test
If we don't hit 98% accuracy, we'll annotate your entire dataset free.
Extract Every Entity That Matters
From gene names to legal case numbers—our linguistic experts catch the aliases, honorifics, and domain jargon that crowdsourcing misses. Get custom entity taxonomies with anonymized PII handling under strict GDPR compliance.
GDPR & Data Protection at Your Personal AI
Protecting personal data is at the core of everything we do. We operate in full alignment with the EU General Data Protection Regulation (GDPR) and apply its principles across all of our global projects.
Privacy by Design
All of our data collection and annotation workflows are designed with privacy and compliance in mind from the very beginning. We only process the minimum amount of personal data required, and every project undergoes a structured review to identify and mitigate privacy risks before launch.
Lawful Basis & Consent
We establish a clear legal basis for each processing activity. Where consent is required, it is gathered transparently, with participants informed about the scope of the project, the purpose of the recordings, and their rights under GDPR. Consent can be withdrawn at any time without penalty.
Data Subject Rights
We respect and enable all rights under GDPR. Requests are handled promptly and without unnecessary delay.
Secure EU Storage
All sensitive data is stored in secure, access-controlled environments within the European Union by default. If cross-border transfers are required, we use the European Commission's Standard Contractual Clauses (SCCs) and ensure equivalent protection.
Vendor & Sub-Processor Management
We maintain a strict register of all sub-processors. Every vendor undergoes a compliance review and is bound by contractual data protection obligations. We never use sub-processors without prior vetting and contractual safeguards.
Continuous Governance
Our compliance framework is not static. We conduct regular internal audits, update our practices in line with evolving guidance from EU regulators, and train our teams to ensure privacy is embedded in day-to-day operations.