LLM Integration
Embed enterprise-grade LLMs into your existing apps, CRMs, and internal tools.
HEU.AI provides AI integration services: we connect AI models such as OpenAI GPT and Anthropic Claude to the apps, CRMs and internal tools you already run, through APIs, MCP servers and retrieval augmented generation (RAG), with guardrails and monitoring so the deployment stays reliable. We are model-agnostic, so model selection comes down to what fits your accuracy, cost and compliance needs. Our generative AI integration services cover API integration, fine-tuning where it helps, agent orchestration, and evaluation and monitoring.
Integration patterns
API integration
Add LLM capabilities to web, mobile, and internal systems via APIs and microservices.
Fine-tuning
Tune a model on your data and tone where it measurably improves results.
RAG hookup
Connect models to your knowledge base with RAG for grounded, source-cited answers. To see why hybrid retrieval matters, read Hybrid Search vs Pure Vector Search.
Agent orchestration
Chain prompts and tools into pipelines that complete multi-step work.
Evaluation & monitoring
Track quality and cost in production so they stay in range as usage scales.
Guardrails
Safety, data-handling, and compliance controls built in before release.
MCP servers and tool integration
An assistant that can only talk is a demonstration. An assistant that can query and act is infrastructure. The difference is tool access, and every organization's systems are different enough that off-the-shelf connectors rarely cover the ones that matter.
We build MCP servers that expose internal systems to the AI layer as controlled, permissioned tools. It is how six coordinated agents operate a construction firm's own files and desktop tools, and how a quoting engine queries internal systems directly without a human relaying the data. A central formatting service can also be registered as a tool on the AI layer, so the assistant can call it as well as other systems calling it by API.
Purpose-built MCP servers
Your internal systems exposed to the AI layer as tools it can actually call, not as documentation it can only describe.
The systems work already lives in
Integrations across CRM, document storage, search, messaging, scheduling, and billing.
Permission boundaries per tool
An agent reads what it should and writes only where it is allowed, defined tool by tool.
Extensible by registration
New capability arrives by registering a tool, not by rebuilding the assistant around it.
Security & compliance
We follow a dedicated security review before every release and controlled data handling. New capabilities slot into your existing web, mobile, and internal systems through APIs and microservices, so you do not have to replace what already works.
Use cases
If the integration is a chatbot, our guide to chatbot development frameworks covers the main options and how to choose one.
AI in your SaaS product
Ship AI features inside an existing application without a rebuild.
Internal copilot
A secure assistant for your team, grounded in your tools and data.
Workflow automation
Automate steps inside your CRM, Slack, or Teams environment.
Our process
Discovery
Map the workflow, model fit, and compliance constraints.
Build
Integrate via APIs, with fine-tuning or RAG where it helps.
Test
Evaluate quality, cost, and security before release.
Deploy
Ship with monitoring so quality holds as usage scales.
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FAQ
Which LLMs can you integrate?
We integrate OpenAI GPT and Anthropic Claude and are model-agnostic: we recommend the model that best fits your accuracy, cost, and compliance needs, with fine-tuning where it helps.
Can you add AI to our existing application?
Yes. We integrate LLM capabilities into existing web, mobile, and internal systems through APIs and microservices, so you do not have to replace what already works.
How do you keep LLM integrations secure?
We follow a dedicated security review before every release and controlled data handling.
Do you handle ongoing monitoring after integration?
Yes. We set up evaluation, monitoring, and optimization so quality and cost stay in range as usage scales.
What are generative AI integration services?
We add generative models such as OpenAI GPT and Anthropic Claude to your existing apps and workflows through APIs, with fine-tuning, RAG, guardrails and monitoring where they help.
Can you connect AI to our CRM and internal systems?
Yes. We build MCP servers that expose internal systems, such as CRM, document storage, search, messaging, scheduling and billing, to the AI layer as permissioned tools.
What does an AI integration project look like?
Four steps: discovery, build, test and deploy. We map the workflow and compliance needs, integrate through APIs, evaluate quality, cost and security, then ship with monitoring.
Add Enterprise AI to What You Already Run
Book a free consultation and we will map the fastest, safest path to GPT or Claude in your stack.