AI Agents · Built for US businesses

AI agents that do real work, not just chat

We design AI agents around a defined task, approved data sources, integrations, human review, and an operational fallback. The selected model follows the requirements, not a sales label.

Model selected by use caseIntegration scope documentedHuman review planned

In 30 seconds

What is an AI agent and what can it do for your business

An AI agent is software built on a large language model (Claude, GPT) that does not just answer questions — it takes actions: updates your CRM, sends follow-ups, drafts proposals, triages support tickets and escalates to a human when needed. We scope the use case, build the agent with your knowledge base, integrate it with your stack and keep tuning it after launch.

  • What we build: support agents trained on your docs, sales agents that qualify and book meetings, back-office agents that process documents and data.
  • Stack: Claude and GPT models, n8n workflow automation, RAG knowledge bases, integration with HubSpot, Slack, WhatsApp and your existing tools.
  • How it works: remote discovery, written scope, access review, evaluation criteria, staged implementation, and an agreed operational handoff.
  • We use it ourselves: our own operations run on the same agents and automations we sell. No slideware.

Use cases

Where AI agents pay for themselves fastest

Customer support

An agent trained on your docs resolves repetitive tickets 24/7 and hands off complex cases to your team with full context.

AI & chatbots →

Lead qualification

Every form, chat or call gets qualified, logged in your CRM and followed up — before your competitor answers.

All services →

Back-office automation

Invoices, reports and data entry processed automatically with n8n workflows plus AI extraction.

Measure the impact →

FAQ

AI agent questions, answered

How much does an AI agent cost?

Cost depends on the task, data sources, integrations, security requirements, human review, and operational support. We quote after those dependencies are clear.

Which AI models do you work with?

The model is selected for the use case, data-handling requirements, evaluation plan, and operating cost. We can work with customer-managed provider accounts when that is part of the agreed architecture.

How long does deployment take?

Timing depends on integration access, data readiness, evaluation criteria, review availability, and the risk of the workflow. The schedule is defined after discovery.

Do you work with US companies remotely?

Yes. YAG provides remote service across US time zones. Communication channels, review cadence, and ownership are agreed for each engagement; this does not imply a local US office.

Your competitors are already automating

Tell us which workflow consumes the most time and where human review must remain. We will identify the information needed to assess it responsibly.