Vacon.AI

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Overview

$1,000+

Min Project Size

< $25/hr

Avg Hourly Rate

2 - 9

Employees

2022

Year Founded

ABOUT VACON.AI

Fixed-price, AI proof of concepts & MVPs in 6 Week

For entrepreneurs and startups seeking AI specialists to embrace technology, analyze data, and tackle difficult problems with a focus on business, this is the place for you. It brings together data scientists, full stack AI professionals, and tech marketers—where technical skill converges with business acumen.

Languages Spoken

English

HIGHLIGHTS

$1,000+

Min Project Size

< $25/hr

Avg Hourly Rate

2 - 9

Employees

2022

Year Founded

Services

Focus

Industries

Clients

Services Provided

15% AI Strategy & Roadmap Consulting

5% BI & Big Data Consulting & SI

15% AI Model Fine-Tuning & Training

15% Machine Learning Model Development

50% Data Strategy Consulting

Portfolio

99.2% Attendance Accuracy with Facial Recognition

Unknown

**The Challenge**: Tracking student attendance at universities presents several difficulties. When done manually, it becomes a tedious and time-consuming process, with some students finding ways to exploit the system. In larger classes, it’s less likely that instructors will remember every individual, making it easier for students to sign in for absent peers. A prominent university client was facing inconsistencies in their attendance process and was wasting valuable time relying on manual attendance records. Keeping an accurate attendance register has long been a challenge for universities using a manual headcount method. **Solution**: Vacon proposed the use of facial recognition technology to automate attendance tracking utilizing existing CCTV systems across the campus. They developed an AI model and web-based software that identifies students as they pass through various entrance areas and approach classrooms. This identification is facilitated by a one-time biometric photo upload to a database for machine learning purposes, requiring only one photo per student for accurate recognition. **How it works**: 1. The Hog model from the Python face-recognition module performs face detection. 2. Detected faces are matched to the photo database using embeddings derived from each image. 3. FaceNet generates facial embeddings for all images, and a specific threshold is set to compare face embeddings with the database. 4. Web sockets provide results on the website, displaying the student’s name, ID number, and photo. **Results**: The system allows instructors to focus on teaching, yielding 100% of their time for educational activities. It achieves 99% accuracy in facial recognition within seconds. Anecdotal evidence indicates a decrease in behavioral misconduct complaints, as students are aware that cameras track their movements and locations.

Call Center: 120% Increase in SDR Dials

Unknown

**The Challenge** A call center employs a team of Sales Development Representatives (SDRs) who aim to achieve daily key performance indicators (KPIs), such as the number of calls made and successful connections—crucial metrics for their role. The issue arises because simply dialing a number doesn’t ensure reaching a person. When calls either go unanswered or are redirected to voicemail, it leads to wasted time and inefficiency. For SDRs, experiencing a series of unanswered calls or calls that go to voicemail can be disheartening and demotivating. The SDR position is demanding, and sustaining peak mental focus is difficult when they can’t engage with a live person. **Solution** Vacon developed a script that dials prospects' numbers and employs an AI model to identify whether a call is answered by a person, goes unanswered, or diverts to voicemail. This "call classifier" AI differentiates between three outcomes: 1. A live human voice 2. No answer (the call simply rings) 3. Voicemail recording. Through training the AI model on these three categories, it successfully connects SDRs to a live individual on every call. **Results** The outcome was a 100% call connection rate—previously unprecedented in the call center sector—along with zero wasted time on unproductive calls. There was a 120% increase in outbound dials, a 23% rise in meetings booked, and a 32% growth in the sales pipeline. SDRs also reported greater job satisfaction and improved morale with the implementation of the AI model.

EdTech: Voice Recognition API Increases DAU by 19%

Unknown

**The Challenge** The client, an EdTech startup, aims to teach young children the alphabet through a mobile application. However, they are uncertain about the progress and knowledge retention of their students using current teaching methods. To improve this, they want to utilize technology by “gamifying” the learning process and effectively tracking student progress. The concept is to incorporate elements that trigger dopamine release into the user experience, making learning fun and engaging, which would lead to increased app usage and greater user retention. **Solution** Vacon suggested integrating a speech-to-text API within the app. This feature would capture the student’s voice and evaluate the accuracy of their pronunciation and recall speed. Users would receive positive reinforcement through collectible badges for achieving specific milestones. Meeting the minimum learning criteria would allow access to the next lesson. **How it works:** Voice activity detection (VAC) was utilized on an audio dataset to identify spoken words from extensive audio files. After segmenting the audio, a deep learning model was developed in Pytorch to classify each clip into one of 10 categories (0 to 9). Upon achieving over 95% accuracy in testing, a Flask API was created and integrated into the mobile application. **Results** The API delivers transcriptions and comparisons within 50 milliseconds with a 95% accuracy rate. Daily Active Users (DAU) increased by 19%, retention rates rose by 12%, and the average session length grew by 32%.

3 more projects

Projects & Clients

Project Size & Rate

Minimum Project Size

$1,000+

Average Hourly Rate

< $25/hr

Pricing Snapshot

Min Project Size

$1,000+

Avg Hourly Rate

< $25/hr

Cost Rating

N/A

What Clients Have Said

"Vacon.AI delivers quality projects within budget and timeline expectations based on verified client feedback."

Based on verified reviews and internal benchmark data

PROJECT BUDGETS

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AI Strategy & Roadmap Consulting

BI & Big Data Consulting & SI

AI Model Fine-Tuning & Training

Machine Learning Model Development

Data Strategy Consulting

Industry Recognitions

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Portfolio

99.2% Attendance Accuracy with Facial Recognition

Unknown

Call Center: 120% Increase in SDR Dials

Unknown

EdTech: Voice Recognition API Increases DAU by 19%

Unknown

3 more projects