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Generative AI integration services for your product and workflows

We bring LLMs, RAG, and AI-generated content into your product and workflows. Claude, OpenAI, and open-source models, with cost controls and guardrails. Where search or content matters, we also handle GEO and AEO so ChatGPT, Perplexity, and Google AI Overviews cite you.

What is generative AI integration?

Generative AI integration is adding large language models, retrieval (RAG), and AI-generated content into an existing product or workflow. It covers model selection and routing, grounding answers in your own data, prompt and eval management, cost caps, and guardrails, so the feature is accurate, affordable, and safe to put in front of customers.

  • LLM integration with Claude, OpenAI, and open-source models.
  • RAG systems that answer from your data and cite the source.
  • Prompt caching, model routing, and spend caps to control cost.
  • GEO and AEO so AI search engines find and quote your product.
  • Proven with Content Compass and AVL Copilot.
Last updated September 2026

How does AI integration work in 2026?

In 2026 the pattern is set: one router in front of several models, retrieval over your own data, and an eval set that runs before every prompt change. Easy requests go to a small, cheap model. Hard ones go to Claude or a frontier OpenAI model. Every answer cites the document it came from, and every call is logged with tokens and cost.

If content or search matters to your business, AI integration now includes GEO and AEO. SEO in 2026 means being cited by ChatGPT, Perplexity, and Google AI Overviews (GEO) and being the quoted answer (AEO). We structure your docs, product pages, and help center so answer engines can read and quote them. That is part of the build, not a separate project.

Outcomes

What do you get?

LLM integration

Claude, OpenAI, and open-source models built into your apps.

RAG and knowledge

Document Q&A, semantic search, and retrieval that stays accurate.

Found by AI search

GEO and AEO so ChatGPT, Perplexity, and AI Overviews cite your pages.

Cost and guardrails

Prompt caching, model routing, and safety controls on every call.

Deliverables

What is included?

LLM integration

Claude, GPT, Llama, and other models integrated through APIs with a router in front.

RAG systems

Document Q&A, knowledge bases, and semantic search with vector databases.

AI workflows

Automated content creation, summarization, classification, and extraction.

Fine-tuning and custom models

Models tuned on your data for domain-specific accuracy.

Evals and guardrails

Scored test sets that run before every prompt change, plus input and output filters.

GEO and AEO

Docs, product pages, and help centers structured so answer engines quote them.

Why us

Why teams pick TechEmulsion

30+ AI products shipped since 2023. Top Rated Plus on Upwork. US LLC in Wyoming. Here is what that gets you:

30+ AI products shipped

Our engineers have shipped 30+ AI products to production. You get code that holds up under real users and is easy to maintain.

Built for your business

We build around how your team already works. No generic templates, no forcing you onto new software.

4 to 8 week ship cycles

Most builds go live in 4 to 8 weeks, not 6 months. You see working software early and often.

Simple to use

Your team should not need training to use what we build. We design every screen and workflow to be obvious.

NDA and security

We sign an NDA before we see anything. Your data stays yours, and we follow security best practices on every build.

Support after launch

We do not disappear after delivery. Ongoing engagements include monitoring, fixes, and updates.

How does the engagement run?

A simple LLM integration is live in 2 to 4 weeks. RAG plus workflows takes 6 to 12 weeks. Both run as fixed-scope projects, with a monthly retainer for evals and model updates after launch.

Not a fit if you want a chatbot bolted on with no data behind it, or a free pilot. We scope a paid proof of concept first.

01.

Discovery

A free 30 minute call. We listen first. No pitch deck.


02.

Plan

We scope the first system that pays for itself and give you a fixed timeline.


03.

Ship and iterate

We build, test on real data, launch in 4 to 8 weeks, then improve it with you.


Questions about Generative AI Integration

Answers from the engineers who do the work. Anything else, ask on a free 30 minute call.

Ready to put an LLM inside your product? Book a call.

Free 30 minute discovery call with Hassan. We listen first. No pitch decks.

See our work

Content Compass

LinkedIn content analysis automated for up to 500 creators

AVL Copilot

40 to 60% less troubleshooting time with a production RAG copilot

Good Food Project

67% less content time, nearly 3x the output