Natural Language Processing
Advanced NLP engineering and applied research to convert text into understanding and value. From large language models to retrieval-augmented generation, we build conversational agents, extraction systems and semantic search tailored to your domain.
What We Deliver
For each engagement we focus on measurable outcomes: product-market fit, reliable models and systems, and an engineering setup for safe, maintainable production. Below are the core features and capabilities we implement as part of this service.
Custom LLM fine-tuning & prompt engineering for domain accuracy
Conversational AI: multi-turn chatbots, assistants and voice agents
Information extraction, entity linking and document understanding
Semantic search & knowledge retrieval (RAG) with vector stores
Text summarization, classification, translation and NLU pipelines
Hybrid retrieval+generation systems with safety, filtering and fact-checks
Pipeline orchestration, batching and low-latency inference
Evaluation frameworks, synthetic data generation and human-in-the-loop tooling
Our Approach
- 1
Discovery & Feasibility
We run a short discovery to validate data availability, define success metrics and create a technical feasibility plan with a clear MVP scope.
- 2
Prototype & Validation
Rapid prototyping to validate model quality and integration assumptions. We include human-in-the-loop evaluation and benchmarks.
- 3
Productionization
Harden the best models into reproducible pipelines, add monitoring, CI/CD, and optimize for latency and cost (edge or cloud deployment as required).
- 4
Scale & Operate
Ongoing improvements, retraining pipelines, A/B testing and performance SLAs.
Technology We Use
We use industry-leading technologies and best practices to deliver high-quality, scalable solutions.
Backend Technologies
- FastAPI for ML serving
- API rate limiting & caching
- Real-time inference
- Model monitoring
AI & Machine Learning
- Large Language Models (LLMs)
- Fine-tuning & prompt engineering
- RAG (Retrieval-Augmented Generation)
- Vector databases (Pinecone, Weaviate)
- spaCy, Transformers libraries
Representative Case Studies
Customer Support AI Chatbot
Built a retrieval-augmented conversational assistant integrated with the client's knowledge base, reducing first-response time and support load.
- First-response time ↓ 60%
- Support ticket deflection ↑ 25%
- CSAT ↑ 9 points
Document Processing AI
Developed NLP system for automated document classification and information extraction from unstructured text.
- Processing time ↓ 90%
- Accuracy: 94%
- Manual work ↓ 85%
Deliverables & Engagement Models
Proof of Value
2–6 week spike to validate feasibility and demonstrate measurable improvement on a target metric.
Product Delivery
Full implementation from prototype to production with monitoring and training pipelines.
Staff Augmentation
Embed our engineers with your team for ongoing development and maintenance.
Frequently Asked Questions
What is the typical project timeline?
Project timeline varies based on complexity and requirements. Small projects take 4-8 weeks, medium projects 2-3 months, and large projects 4-6 months or more. We provide detailed timelines after understanding your specific needs.
Do you offer post-launch support?
Yes, we provide comprehensive post-launch support including bug fixes, performance monitoring, security updates, and feature enhancements. We offer various support packages to meet your needs.
What is your pricing model?
We offer flexible pricing models including fixed-price projects, time & materials, and retainer agreements. Contact us for a customized quote based on your specific requirements.
How do you ensure project quality?
We follow best practices including code reviews, automated testing, continuous integration, quality assurance testing, and regular client feedback sessions to ensure the highest quality deliverables.
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Ready to Get Started?
Book a free discovery call and receive a tailored roadmap and estimate for your project.