Real-Time AI Voice Agent. Cold Calling Automation Case Study

Real-Time AI Voice Agent for Cold Calling

We developed a real-time voice-to-voice AI agent for the client, one of the top affiliate CPA networks. It delivers human-like conversations, handles noisy environments, and integrates with the client’s CRM and ATS. Trained on sales data, it boosts performance with <450 ms response time and a 1:1–1.5 sales quality ratio vs. human agents.

1:1–1.5

Sales quality ratio vs. human agents

450

voice bot response latency — faster than human reaction time

About the client

Our client is a leading affiliate CPA network, recognized for offering the best conditions for partners and advertisers. Focused on delivering high-quality leads and maximizing campaign performance, they continuously invest in innovation to maintain their competitive edge in the affiliate marketing industry.

Tech stack

Silero VAD

Whisper Large

Gemini

ElevenLabs

SIP

The client's needs

The client set out to integrate AI into their core workflows to stay ahead of the competition, aiming to boost efficiency, elevate customer interactions, and future-proof their operations. They needed a voice-to-voice AI agent capable of real-time, human-like conversations, trained in sales techniques and product knowledge, resilient in noisy environments, and fully integrated with their custom CRM and ATS systems to automate data flows and accelerate performance across the board.

Challenges & solutions

Challenge

Build a real-time, natural-sounding voice-to-voice AI agent as close as possible to human speech.

Solution

We selected a voice model with human-like sound quality and developed an AI agent optimized for real-time, natural conversations. The AI voice was fine-tuned to be expressive and lifelike, ensuring more natural interactions.

Challenge

Train the AI voice bot on sales techniques and product knowledge.

Solution

Using data from hundreds of hours of sales calls, scripts, and marketing materials, we built a custom database via Retrieval-Augmented Generation (RAG). Leveraging a fine-tuned LLM and the LangChain framework, we developed a reliable AI capable of handling real-world sales conversations, objection handling, and upselling scenarios.

Challenge

Ensure voice recognition in noisy environments during real-time calls.

Solution

We developed a custom noise suppression framework using adaptive models, allowing the AI to accurately recognize and process speech even during calls with background noise. This ensures clear voice recognition and natural conversation flow, even in suboptimal acoustic conditions.

Challenge

Seamlessly integrate with the client’s custom CRM and ATS systems

Solution

We integrated the voice agent with the client’s CRM and ATS, enabling real-time call logging, automated data synchronization, and streamlined workflows across platforms.

Challenge

Solution

Challenge

Solution

Challenge

Solution

Challenge

Solution

Luxury Retailer AI Demand Forecasting Implementation

Results

The client aimed to gain a competitive edge by embedding AI into their workflows, enhancing efficiency and improving customer interactions.

We built a custom AI voice agent capable of real-time, two-way voice interaction with human-level responsiveness. With sub-450 ms latency and operating costs under $4/hour, it delivers scalable, natural conversations.

Matching or exceeding human performance with a 1:1–1.5 sales quality ratio, the solution enables scalable outreach, reduces cost per interaction, and ensures consistent conversion results. It enhances operational efficiency and unlocks new revenue streams, turning AI into a strategic asset.

AI-Powered Cold Calling: Real-Time Voice-to-Voice Conversations

The Way We Deal with Your Task and Help Achieve Results

Step 1 of 5

Web development discovery

It's a good time to get info about each other, share values, and discuss your project in detail. We will advise you on a solution and help you understand if we are a perfect match for you.

Step 2 of 5

Discovering And Feasibility Analysis

One of our core values is flexibility. Hence, we work with either one-page high-level requirements or a whole pack of tech docs. In AI demand forecasting case studies, there are numerous models and approaches, so at this stage, we perform a set of interviews to define project objectives. We elaborate and discuss a set of hypotheses and assumptions. We create a solution architecture, a project plan, and a list of insights or features to achieve.

Step 3 of 5

Solution Development

The work starts with data gathering, data cleaning, and analysis. Feature engineering helps to determine your target variable and build several models for the initial review. Further modeling requires validating results and selecting models for further development. Ultimately, we interpret the results. Nevertheless, demand forecasting solution modeling is a process requiring many back-and-forth iterations. We are result-focused, as it's also one of our core values.

Step 4 of 5

Solution Delivery

AI demand forecasting solutions can be a list of insights or models that consume data and return results. Though we have over 15 years of expertise in data engineering, we expect the client's participation in the project. While modeling, we provide midterm results so you can always see where we are and provide us with feedback. By the way, a high level of communication is also our core value.

Step 5 of 5

Support And Continuous Improvement

We understand how crucial the solutions that we code for our clients are! We aim to build long-term relations, providing guarantees and supporting agreements. Moreover, we are always happy to assist with further developments, and statistics show that 97% of our clients return to us with new projects.

Success stories

Check out a few case studies that show why DATAFOREST will meet your business needs.

All Success Stories

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customer retention boost

25%

profit growth

Christopher Loss

CEO Dayrize Co, Restaurant chain

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The team has met all requirements. DATAFOREST produces high-quality deliverables on time and at excellent value.

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increase in sales

100%

dead zones removed

Jared D.

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DATAFOREST provides meaningful shopper-behavior Insights. They are very responsive and effective, trying to engineer and offer the best fit solution.

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32%

client experience improved

43%

boosted speed of the new workflow

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Reporting & Analysis Automation with AI Chatbots

The client, a water operation system, aimed to automate analysis and reporting for its application users. We developed a cutting-edge AI tool that spots upward and downward trends in water sample results. It’s smart enough to identify worrisome trends and notify users with actionable insights. Plus, it can even auto-generate inspection tasks! This tool seamlessly integrates into the client’s water compliance app, allowing users to easily inquire about water metrics and trends, eliminating the need for manual analysis.

100%

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