The AI marketing agency
that works while you sleep.

An AI marketing agency builds and deploys artificial intelligence systems that automate marketing and business workflows. This includes AI chatbots, lead qualification bots, automated content pipelines, LLM integrations, and RAG systems that pull from your own data. The goal is to replace high-repetition tasks so your team focuses on work that actually requires a brain.

AI marketing automation connects your existing tools (CRM, email, ad platforms, support desk) and introduces intelligent decision-making at each step. Instead of rules-based "if X then Y" flows, AI reads intent, classifies inputs, and acts accordingly. Examples include AI that routes inbound leads by fit score, writes first-draft ad copy from a brief, or escalates support tickets based on sentiment.

High-repetition tasks with a predictable pattern are the best candidates: answering common customer questions, qualifying inbound leads, generating first-draft copy, tagging and routing support tickets, extracting data from documents, and reporting. If someone on your team does the same thing more than 20 times a week and it follows a pattern, AI can likely handle it.

Anything repetitive and rule-based is a candidate: answering common customer questions, classifying emails, extracting data from documents, generating reports, routing tickets. The rule of thumb is simple. If someone on your team does the same thing more than 20 times a week, it's probably automatable. We'll tell you if something isn't a good fit.

Most projects go from kickoff to production in 3-6 weeks. You'll see a working prototype in the first week. Simple workflow automations can be live in under 2 weeks. Complex RAG systems or custom LLM integrations take closer to 6-8 weeks. We scope tightly and build incrementally, so you're never waiting months with nothing to show for it.

Your data stays yours. We use enterprise API tiers from OpenAI and Anthropic where your data is not used for model training. For sensitive industries like healthcare and finance, we can deploy on your own infrastructure or use Azure/GCP private endpoints. Data masking and PII filtering are standard. Every project includes a data handling agreement.

We're model-agnostic. GPT-4 and GPT-4o handle most general-purpose tasks, Claude is better for long-document processing, and Gemini covers multimodal work. For cost-sensitive applications we use smaller models like GPT-4o-mini or Claude Haiku. We often run multi-model setups: hard tasks go to the bigger model, routine ones use something cheaper and faster.

Yes. AI systems degrade over time as your business changes, so they need monitoring. We offer maintenance packages covering performance monitoring, model updates, and prompt refinement based on real usage data. You can also bring it in-house if you prefer. We document everything and do a proper handover.

That's the whole point. We connect to whatever you're already using: Salesforce, HubSpot, Zendesk, Slack, Shopify, custom APIs, databases. If it has an API, we can integrate. We build on top of what you have.

It's a real concern. For customer-facing applications, we use RAG to ground responses in your actual data, not the model's general knowledge. We add confidence scoring so the system knows when it's unsure and escalates to a human. We also build in guardrails: topic boundaries and response validation. Nothing goes live without testing against real scenarios from your business.

Size matters less than repetition. A 10-person company where 3 people spend half their day on the same tasks has a stronger case than a 500-person company where everyone does unique work. If your team does the same thing repeatedly and it follows a pattern, automation saves time regardless of headcount. We've built systems for teams of 5 and teams of 500.