NLP Development
Natural language processing turns unstructured text and speech into structured signal — entities, sentiment, intent, summaries — that your systems can act on. We build NLP pipelines that hold up on messy real-world language, not clean benchmark datasets.
0%
Avg. Classification Accuracy
0+
Languages Supported
6-10 wks
Typical Engagement
1000s/min
Throughput
What's Included
NLP pipeline for the target task (extraction, classification, summarization, etc.)
Evaluation report with accuracy benchmarks
Production API endpoint
How We Work
01
Text Data Audit
We review sample text or speech data to understand structure, noise, and language coverage.
02
Pipeline Design
We select the right approach — classical NLP, fine-tuned transformer, or LLM — for accuracy and cost.
03
Training & Evaluation
The pipeline is trained and benchmarked against held-out real examples, not synthetic ones.
04
Integration & Scaling
We deploy as an API and load-test it against your expected volume.
What You'll Receive
- NLP pipeline for the target task (extraction, classification, summarization, etc.)
- Evaluation report with accuracy benchmarks
- Production API endpoint
- Monitoring for accuracy and latency
- Technical handover documentation
How Engagements Typically Work
Every project starts with scoping — here's the shape most engagements for this service take.
Proof of Concept
A 2-week sprint validating accuracy on your real text samples before committing to production.
Production Build
Full pipeline engineering and deployment — typically 6-10 weeks depending on scope.
Ongoing Retainer
Monthly monitoring and retraining as language patterns or business categories shift.
Technologies We Use
The tools and platforms our NLP Development team works in day to day.
NLP
Infra
Frequently Asked Questions
Yes — we've shipped multilingual pipelines using both fine-tuned multilingual models and LLM-based approaches, depending on accuracy needs.
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