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Reduce Order Errors. Cut Manual Work. Serve More Customers Without Lifting a Finger.

Imagine reducing human intervention in restaurant bookings by 90%, while giving every caller a smooth, intelligent ordering experience—without hiring another soul.

Client

USA-based Restaurant Operator

Industry

Enterprise (Restaurant Technology / AI Automation)

Timeline

1 month

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Quick Snapshot

Brief

Challenges

Solution

Impact

Consider This

Quick Snapshot

A restaurant operator in the USA was struggling with inaccurate AI order bookings due to noisy call audio. We streamlined the transcription pipeline by properly decoding audio from Twilio’s format, which resulted in 95%+ transcription accuracy and a fully automated ordering workflow.

Brief

In high-volume restaurants, every second matters. But when AI assistants mishear your customer’s “pepperoni pizza” as “macaroni with peanuts,” things go from delicious to disastrous.

That’s exactly what a restaurant owner in the USA, was facing. The idea was strong: automate order booking using an AI assistant that answers customer calls, confirms their menu choices, and stores the order in a database.

But the execution hit a snag. The audio streamed from Twilio was noisy and incorrectly formatted, leading to laughably inaccurate transcriptions.

We diagnosed the real issue fast: the audio stream was in Mulaw format but being handed to the transcription model as a WAV file, with no actual conversion. This would be like passing a badly scribbled order note to a Michelin chef and expecting fine dining.

Once we implemented the proper audio conversion before transcription, the results transformed overnight, bringing clarity to the chaos and making the entire ordering process truly hands-free.

Challenges

Inaccurate Transcriptions Due to Noisy Audio

The core AI was in place, but what it heard… wasn’t pretty. Twilio streamed call audio in Mulaw format, but it was passed to OpenAI Whisper without decoding, leading to garbage in, garbage out.

Lack of Audio Format Handling

The restaurant’s pipeline didn’t include logic to convert or clean incoming audio streams, resulting in inconsistent and error-filled customer orders.

Manual Overrides Were Defeating the Purpose

Staff had to intervene regularly to fix incorrect transcriptions, eliminating the very efficiency AI was meant to bring.

Solution

We optimized the audio processing pipeline by inserting a crucial—but often overlooked—step: proper audio format conversion.

Audio Stream
Conversion

We decoded Twilio’s Mulaw stream into actual WAV files before sending them for transcription.

Real-Time
Whisper Integration

Once the audio was clean, OpenAI Whisper performed flawlessly, transcribing orders with more than 95% accuracy.

Database
Integration

Finalized orders were stored directly in the client’s backend, ready for the kitchen, no human in the loop.

Impact

35%

Accuracy

Increased transcription accuracy from ~60% to over 95% with AI-powered conversion.

90%

Intervention

Reduced manual intervention per order from frequent to rare.

50%

Speed

Cut average order completion time from 4–6 minutes to under 2 minutes.

80%

Dependency

Lowered human staff dependency from high to minimal.

Impact-of-Fix-on-Order-Booking-Metrics

Consider this:

Before AI

Saturday nights once meant constant phone calls, stressed staff, and frequent order corrections. Miscommunications were common, with requests like “Sprite” being mistaken for “fight” or, in one particularly memorable case, “paneer tikka” recorded as “banana pizza.”

After AI

Now, the AI ensures accuracy from the start. It processes orders clearly despite background noise, varied accents, or hurried customers. The result is precise, ready-to-execute orders, allowing the team to focus on kitchen operations rather than clarifying errors. The same staff. The same high-paced environment. Only now, it runs with a far smarter system in place.

Ready to serve more customers, not more headaches?

Let’s talk. In 15 minutes, we’ll show you how AI can clean up your call orders, boost efficiency, and leave your team free to do what they do best: serve great food.

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Our Solutions in Action

Read how we have transformed businesses along the way.

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