LLM Integration

LLM Integration & API Development

Add LLM intelligence to your existing product or platform without rebuilding everything.

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Overview

Add LLM intelligence to your existing product or platform without rebuilding everything.

We integrate large language models into your existing software, workflows, and platforms — clean APIs, streaming responses, cost optimization included.

Who this is for

Built for these teams and businesses

Software companies adding AI featuresProduct teams with existing codebasesEnterprises integrating AI into internal toolsDevelopers who need AI expertise

Use cases

What we build for you

◆Adding AI chat to existing SaaS products
◆LLM-powered document processing in existing workflows
◆AI-generated content in CMS and marketing platforms
◆Internal search and Q&A powered by LLMs
◆AI features in mobile and desktop apps

Problems we solve

— Team knows it needs AI but isn't sure how to integrate it cleanly
— Worried about cost, latency, and reliability at scale
— Previous LLM integrations were slow or expensive
— Need to add AI without breaking existing product

Tech stack

Platforms and tools we use

OpenAI APIAnthropic Claude APIGoogle GeminiAzure OpenAIAWS BedrockLocal/open-source LLMs

What you get

Deliverables

◆ Integration architecture

◆ API build and deployment

◆ Cost and performance optimization

◆ Documentation

Typical timeline: 1–6 weeks

Process

How an engagement works

Discovery call

We map your workflows, understand your tools, and identify the highest-ROI agent opportunity in your business.

Architecture design

We design the agent: inputs, outputs, integrations, error handling, and the logic that makes it reliable in production.

Build and integrate

We build the agent, connect it to your tools and data, and run it through real scenarios — not sanitized demos.

Test and harden

We stress-test edge cases, add monitoring, and make sure the agent degrades gracefully when something unexpected happens.

Deploy and hand off

We deploy to production, set up alerting, and train your team to manage and iterate on the agent going forward.

Why Lumeor

What to expect working with us

◆Production deployments only — we don't hand over prototypes and call them done
◆We set up monitoring and alerting on every agent we ship
◆Transparent about what AI can and can't do reliably
◆Model-agnostic — we pick the right tool for your use case, not what we're certified in
◆We document everything so your team can maintain and extend what we build
◆30-day stabilization period included in every engagement
◆We've shipped agents for businesses across every major US industry

FAQ

Common questions

How long does it take to build and deploy an AI agent?

Most simple agents (single workflow, clear inputs/outputs) are live in 1–2 weeks. More complex agents with multiple integrations or multi-agent architectures take 3–8 weeks. We'll give you an accurate timeline after our first call.

What happens if the agent breaks after you deliver it?

We include a 30-day stabilization period in every engagement. If something breaks, we fix it. We also set up monitoring and alerting so we catch issues before you do. Post-stabilization support retainers are also available.

Can you build agents that connect to my existing software?

Yes — that's the norm, not the exception. We integrate with CRMs, ERPs, ticketing systems, communication tools, databases, and custom APIs. If it has an API or webhook, we can connect an agent to it.

Which AI models and platforms do you use?

We're model-agnostic and platform-agnostic. We use OpenAI, Anthropic Claude, Google Gemini, and open-source models depending on the use case. For automation, we commonly use n8n, CrewAI, LangChain, and custom Python builds.

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