Generative AI

Generative AI Integration Services

Embed GPT-powered features into your US product with confidence — retrieval pipelines, guardrails, cost controls, and UX that enterprise buyers expect.

50+Projects Delivered
USMarket Focus
24/7Dev Coverage

What's Included

  • GPT API integration in weeks
  • RAG document Q&A
  • Cost & usage dashboards
  • Enterprise guardrails

Why Hire GKAI Studio

Copilot UX

Chat and assistant interfaces embedded in your US SaaS product.

Document Q&A

RAG over PDFs, wikis, and support docs with citations.

Versioned Prompts

Prompts treated as code — reviewed, tested, and deployed.

Cost Control

Token budgets, caching, and model routing for US scale.

Integration, Not Experiments

We integrate LLMs into existing US SaaS and internal tools with versioning, evaluation datasets, and fallbacks — so features stay reliable when models update or traffic spikes.

  • Chat and copilot interfaces in React
  • Document Q&A with retrieval-augmented generation
  • Structured JSON outputs for automated workflows
  • Usage metering and cost dashboards for finance teams
  • Feature flags and gradual rollout to US user segments

Business Outcomes for US Products

US clients integrate generative AI to reduce support tickets, accelerate sales research, automate document review, and power internal knowledge search — with measurable before/after metrics on every rollout.

Our Development Process

Every US engagement follows a proven four-phase delivery model — from discovery through production launch on AWS.

Discovery

Requirements workshop, technical audit, and architecture proposal aligned to US business goals.

Design

UX flows, API contracts, database schema, and sprint roadmap with clear milestones.

Build

Agile development with weekly demos, code reviews, and staging environments.

Launch

AWS deployment, monitoring, documentation, and post-launch support handoff.

Tech Stack

We select technologies based on your US product requirements, team capabilities, and long-term maintainability.

OpenAIGPT-4RAGLangChainReactPythonVector DB

Case Studies & Resources

Frequently Asked Questions

A focused MVP integration typically takes 4–8 weeks depending on data readiness, authentication, and compliance requirements for US deployments.

OpenAI, Azure OpenAI, and Anthropic — we select based on latency, cost, data residency, and US enterprise procurement requirements.

RAG with versioned knowledge bases, constrained JSON outputs, evaluation suites, and human review on high-risk customer-facing responses.

Yes. We add API microservices and React components incrementally, preserving your current auth, billing, and user models.

We implement logging, PII redaction, retention policies, and documentation that supports US security and vendor reviews.

Ready to Build for the US Market?

Tell us about your project scope, timeline, and stack. GKAI Studio responds within one business day.

Get in Touch