Case Study - AI agents that think, act, and execute—in real time

Overview

Traditional automation promised efficiency but delivered frustration. IVR trees that loop forever. Chatbots that can't understand context. Systems that force customers to repeat themselves. Atlantis came to us with a simple question: what if AI agents could actually work?

The answer is real-time AI with tool calling. Agents that listen, understand, and act—simultaneously. They don't queue your request for processing. They handle it live, mid-sentence if needed. Query a database. Update a record. Trigger a workflow. Book an appointment. All while maintaining natural conversation that feels genuinely human.

OpenAI's Realtime API made this possible. The latency is imperceptible. The comprehension is remarkable. And the ability to call tools—to actually do things in the world—transforms these from conversational novelties into genuine digital workers.

What we did

The Real-time Difference

What makes this different from every other "AI assistant" you've seen? Real-time processing and tool calling. Here's what that actually means:

Imperceptible Latency — Powered by OpenAI's Realtime API, conversations flow naturally. No awkward pauses while the AI "thinks." Responses begin as soon as you stop speaking—sometimes before. The experience is indistinguishable from talking to a sharp, well-informed human.

True Tool Calling — These agents don't just talk. They act. Mid-conversation, they call functions: check inventory levels, look up order status, verify account details, process refunds, schedule appointments, trigger workflows. Each tool call executes in milliseconds and the agent incorporates results seamlessly into the conversation.

Contextual Intelligence — The agent maintains perfect memory of the entire conversation. It tracks what was said, what actions were taken, what's still pending. It knows when to ask clarifying questions and when it has enough information to act. It understands nuance, sarcasm, urgency.

Autonomous Decision Making — Given the right tools and permissions, these agents make decisions. Not rigid if-then logic, but genuine reasoning about the best course of action. Should this order be expedited? Does this situation warrant an exception? Is this caller's request valid? The AI evaluates and acts.

Technical Architecture

Real-time Speech Pipeline — Audio streams bidirectionally over WebSockets. The AI processes speech continuously, not in discrete chunks. Interruptions are handled gracefully—the agent stops, listens, adapts. Turn-taking feels natural because it is natural.

Tool Registry & Execution — Every capability is a tool: database queries, API calls, system updates, notifications. Tools are defined with schemas, permissions, and guardrails. The agent selects and sequences tools autonomously based on the task at hand.

Workflow Orchestration — Complex operations spanning multiple systems execute as coherent workflows. The agent coordinates across CRM, inventory, billing, scheduling—whatever systems matter. Failures are caught, alternatives are tried, edge cases are handled.

Continuous Learning — Every conversation improves the system. We analyze patterns, refine tool definitions, adjust agent instructions. The platform gets smarter—not just at conversation, but at execution.

Beyond Customer Service

The transformation goes beyond handling calls. These agents represent a new category: AI workers that execute workflows with superhuman speed and consistency.

A customer calls about a missing shipment. The agent identifies them, pulls their order history, checks tracking across carriers, identifies the delay, calculates compensation per policy, applies a credit, triggers a replacement shipment, sends confirmation emails—all in under a minute. A human doing this same workflow: 10-15 minutes minimum, assuming they don't get distracted.

This isn't incremental improvement. It's a fundamental shift in what automation can accomplish. Real-time AI with tool calling isn't just answering phones. It's working.