Custom LLM integration, RAG pipelines, AI agents, and computer vision — built by senior engineers in Vietnam.
Deliverables
Production AI
There's a massive gap between an AI demo and a production AI system. A demo calls the OpenAI API and returns a response. A production system handles error states, manages rate limits, enforces cost controls, and includes monitoring and alerting — so your team knows when something breaks before your users do.
The same gap exists across every AI pattern:
Production RAG needs a deliberate chunking strategy, retrieval tuning, re-ranking, and hallucination guards. Without these, your system returns confidently wrong answers — the worst possible outcome for enterprise AI.
AI agents need tool-use architecture, memory management, and fallback logic. An agent that can't gracefully handle a failed API call or an unexpected user input isn't ready for production — it's a liability.
A production LLM system manages token budgets, implements caching layers, handles model failover, and logs every interaction for debugging and compliance. Cost without controls can spiral from $500/month to $50,000/month overnight.
Most “AI development agencies” bolt LLM APIs onto existing apps and call it AI development. NKKTech architects from scratch — designing systems that are observable, cost-controlled, and built to scale from day one.
Technical Guide
Most enterprise projects need RAG. Fine-tuning is often oversold by agencies looking to increase project scope. We'll tell you which is right for your use case on the discovery call — honestly, even if it means a smaller project.
Tech Stack
Process
We audit your data, workflows, and goals to find the highest-impact AI opportunities.
Detailed technical proposal with architecture, timeline, and fixed-scope pricing within 3 days.
Senior engineers build iteratively with weekly demos. Direct Slack access to your tech lead.
Production deployment, documentation, monitoring setup, and optional ongoing support.
We work with OpenAI GPT-4, Anthropic Claude, Llama, Mistral, and can fine-tune open-source models for your specific use case.
RAG (Retrieval-Augmented Generation) connects LLMs to your proprietary data — documents, databases, APIs. If your AI needs to answer questions about your business data, you need RAG.
Typical projects run 10–16 weeks. Simple LLM integrations can ship in 6 weeks. Complex multi-agent systems may take 20+ weeks.
Yes — about 40% of our clients are non-technical founders. Our discovery process is designed for it: you describe the business problem, we translate it into a technical architecture. You'll receive a plain-English proposal with clear deliverables, timelines, and pricing. During the build, weekly demos let you see progress without needing to read code. Your tech lead explains every decision in business terms.
Pricing
AI development projects at NKKTech typically fall into three tiers. Every engagement starts with a free scoping call — you receive a binding, fixed-scope price before any work begins.
Single API integration, basic RAG, prompt engineering
4–8 weeks
Multi-source RAG, AI agents, custom UI
10–16 weeks
Multi-agent systems, fine-tuning, enterprise infra
20–40 weeks
All projects are fixed-scope — you receive a binding price before signing. No T&M billing, no scope creep. If requirements change mid-project, we re-scope and re-price transparently.
See full pricing detailsIndustries
Automated document processing, fraud detection, compliance reporting. We build SOC 2-ready AI systems that integrate with existing banking middleware for KYC/AML automation and regulatory filing extraction.
AI-powered sales automation, customer support agents, data analytics. We help SaaS teams embed AI features directly into their product — smart search, AI-generated reports, and natural-language querying.
Clinical document extraction, patient intake automation, scheduling AI. HIPAA-compliant AI pipelines for health tech platforms, lab report parsing, and structured data extraction from medical records.
Product recommendation engines, inventory AI, customer service bots. Semantic search that understands intent (not just keywords), dynamic pricing models, and personalized support chatbots trained on your catalog.
Predictive maintenance, quality control vision, supply chain AI. Computer vision for defect detection, IoT data analysis for equipment health monitoring, and demand forecasting models.
Personalization engines, content generation, search & discovery. AI-powered recommendations, user behavior analysis, and intelligent content curation that keeps users engaged.
Why NKKTech
Every engineer on your project has 5+ years of experience. No juniors learning on your budget. Our senior-to-total ratio is 100% — not the 30–40% you'll find at typical offshore firms.
You receive a binding price before signing. No hourly billing, no scope creep, no surprise invoices. If the scope changes, we re-price transparently before continuing.
From signed proposal to your first standup in 14 days or less. We pre-allocate engineering capacity so you don't wait months for availability.
You talk directly to the engineer building your system — not an account manager or project coordinator. Daily Slack access, weekly demos, zero communication layers.
We sign your NDA before the first discovery call. Your IP, data, and business logic are protected from day zero — not after you've already shared everything.
Related Case Study
Built an LLM pipeline with OCR, classification, extraction, and validation — replacing 40+ hours/week of manual document review per analyst.
$200K/year saved · 95% accuracy
View Case Study