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.
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.
Who we serve
Who is this for?
SaaS Companies
AI features shipped inside your product in weeks, not quarters.
See the SaaS Companies page
Digital Marketing Agencies
AI content and reporting features built into the tools you sell clients.
See the Digital Marketing Agencies page
E-commerce and DTC Brands
Product description engines and AI support grounded in your catalog.
See the E-commerce and DTC Brands page
Software Founders
Your first AI feature built right, without an ML hire.
See the Software Founders page
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.
By industry
Where this shows up by industry
SaaS Companies
AI features for funded SaaS
Ship an AI feature in 6 weeks on a paid proof of concept. Production-grade.
Open page
E-commerce and DTC Brands
AI for Shopify brands
Support chatbots and product description engines grounded in your catalog.
Open page
Free tool
Cart recovery calculator
See what abandoned carts cost you before adding AI recovery.
Open page
Digital Marketing Agencies
AI Content Engine
Deliver 8 blog posts a month without burning out your writers
See the offer
Digital Marketing Agencies
Ad Creative Engine
Run 10x more ad variations without a bigger creative team
See the offer
Digital Marketing Agencies
Programmatic SEO
Rank for 1,000 long-tail keywords without 1,000 writers
See the offer
Digital Marketing Agencies
Content Repurposing Workflow
Turn one piece of content into 12 before your next client call
See the offer
Digital Marketing Agencies
AI Support Chatbot
Stop answering the same client questions 40 times a month
See the offer
Software Founders & Builders
Voice Agent Integration
Ship a real-time voice agent your users want to call
See the offer
All industries
Every industry we serve
Marketing agencies, software founders, ecommerce brands, SaaS companies, and home services. One page per industry.
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