AI Sales Call Analyzer

@mubeenm5026

With your AI Sales Call Analyzer project, I can confidently say that my team at Web Crest possesses the perfect amalgamation of skills and experience to bring your idea to life. With a rich background in AI & Automation and a pronounced expertise in Node.js and React.js, we have crafted several similar applications that integrate with third-party APIs to process and summarize large chunks of data, just like you need. Our past projects will help us devise effective dataflow and use databases like MongoDB for recording the results. An example of one such project involved creating a voice transcription application similar to your requirements. We chained multiple services together including depNoise for noise reduction, Google speech-to-text API for transcription, and another customization layer for summarizing specific parts. With this application too, we ensured the generated transcript was timestamped for easy navigation and exported formatted JSON as backup. Our commitment lies not only in meeting the required specifications but also in unlocking additional value through our solutions. On top of delivering a user-friendly, visually driven dashboard for your sales team to easily navigate through information, we also understand the importance of data backups so we provide them as well. If chosen, I can promise you not just an MVP matching your outlined expectations but also a future-proof and scalable system that would continue to grow with your needs. Let's get started!

@oleksiishev

Hello! I am a San Diego-based senior software engineer specializing in both frontend and backend development, with over 10 years of experience building robust systems. I carefully reviewed your project description for the AI Sales Call Analyzer and believe I can deliver a solution that meets your needs. Plan: a Node.js/Express API with an async job queue for long audio, Whisper for STT, and a compact LLM (GPT‑4o‑mini) to extract sentiment and next steps. Results go to MongoDB and a clean React dashboard with timestamped segments and a JSON export. Providers and prompts stay configurable so you can optimize cost/latency over time; uploads are normalized via ffmpeg with clear processing states. Quick checks: 1) Do you have a preferred STT/LLM (Whisper, Gemini, AssemblyAI), or should I pick based on price and speed? 2) What’s the typical call length, and do you need speaker labels/diarization in this phase? Let's connect to discuss your project in detail — I'm excited about the possibility of collaborating! Oleksii

@monicasynthesis

Hello ✋, I’ve gone through your job description and understand that you’re looking to build a system that turns recorded sales calls into actionable insights, highlighting customer sentiment, interest, and next steps. With 5+ years of experience in Node.js development, AI integrations, and dashboard design, I’ve successfully completed similar projects that automate workflow insights from audio content. What I can help you with: • Build a Node.js backend to handle audio uploads (MP3, WAV, etc.) and run AI transcription via Whisper, Gemini, or a similar API • Implement a summarization layer that extracts buyer sentiment, interest cues, and agreed-upon action items • Store results in MongoDB and present them in an intuitive dashboard with timestamped transcripts, summary blocks, and JSON export options Warm regards, Monica Bhatia

@happycoderz

As Happy Coders, we bring to the table a wealth of experience in web development and design including our strong expertise in JavaScript and PHP. We understand the power of automation in enhancing efficiency and facilitating better learning experiences, which is why your project aligns so beautifully with our skill set. To break it down, we can create for you a node.js-based transcription service that utilizes popular AI APIs like Whisper or Gemini for speech-to-text conversions. Once the transcript is generated, our team will develop a summarization layer that not only distills vital information but also intelligently tags sections indicative of buyer interest or hesitation while highlighting agreed action items. All data will then be stored securely in MongoDB and presented to your reps via an intuitive dashboard accompanied by a search feature and export option. Aside from saving your reps valuable time on going through lengthy sales calls, this solution will enable them to dive straight into critical segments that require attention. It's all about optimizing your sales process for better results while retaining analytical data for future use. We commit to delivering a working MVP within a reasonable timeline without compromising on quality. When you choose Happy Coders, you're choosing an exhilarating collaboration that will make your life easier, support your cause, and lead you to more glory and success.

@DigitalNightOwl8

Hi There , Good afternoon! I’ve carefully checked your requirements and really interested in this job. I’m full stack node.js developer working at large-scale apps as a lead developer with U.S. and European teams. I’m offering best quality and highest performance at lowest price. I can complete your project on time and your will experience great satisfaction with me. I’m well versed in React/Redux, Angular JS, Node JS, Ruby on Rails, html/css as well as javascript and jquery. I have rich experienced in MongoDB, AI Text-to-text, Node.js, Redis, PHP, JavaScript, AI Model Development, React.js, Software Architecture and AI Chatbot Development. For more information about me, please refer to my portfolios. I’m ready to discuss your project and start immediately. Looking forward to hearing you back and discussing all details.. Hope to hear from you soon

@UzeeTech

As an experienced Full-Stack Developer with a specialization in AI development and Node.js, I am well equipped to tackle your project on "AI Sales Call Analyzer" comprehensively. Drawing on my knowledge in using Whisper, Gemini and other AI APIs, I can help you develop an efficient system that not only converts audio files to transcripts but also fulfills your required summarization layer proficiently. Moreover, my 7+ years of experience have exposed me to various technologies such as React.js and Flutter - skills that would be instrumental when creating a visually appealing interface for your platform. Importantly, I strongly value communication and my clients have consistently appreciated the clarity I bring throughout projects including daily updates and realistic timelines. This has resulted in an impressive 98% on-time delivery rate - a testament to my reliability. In conclusion, if you choose to work with me, not only will you be working with someone who has proven experience with the core technologies required, but also someone who is deeply committed to delivering exceptional results within the given timeframe. Let's collaborate and create an AI Sales Call Analyzer that not only transcribes calls but also succinctly provides insightful summaries for better sales learnings. Looking forward to speaking with you soon.

@abdf2010

Hey, I liked your project, AI Sales Call Analyzer and believe I can help you with the project. With my background in PHP, JavaScript, Software Architecture, I'm confident I can meet your requirements. Would be glad to go over specifics if you're interested.

@mariamz24

Hello, We would like to grab this opportunity and will work till you get 100% satisfied with our work. We are an expert team which have many years of experience on PHP, JavaScript, Software Architecture, Node.js, Redis, React.js, MongoDB, AI Text-to-text, AI Chatbot Development, AI Model Development Lets connect in chat so that We discuss further. Thank You

@tamannarajput18

With over five years of experience working with Node.js and MongoDB, I am confident in my ability to tackle your project. Having worked on numerous projects that involved chaining Node.js with APIs like Whisper, I fully understand how to extract and process data from audio files. From your flowchart, I've identified key stages such as the conversion of audio files into text, creating a summarization layer, tagging significant segments, and displaying the results on a useful dashboard. My knowledge in MEAN/MERN stack development will be particularly valuable here as it facilitates the creation of real-time applications with powerful features like data import/export - exactly what you need in a dashboard. Moreover, I appreciate your emphasis on reliability and scalability. My background in building scalable applications and automating business processes can be viewed as a testament to those standards. Hence, by choosing me for this project, you're not just getting someone proficient in technologies like React.js, Angular, Node.js, or MongoDB; but also someone dedicated to delivering robust solutions that can grow with your business. Let me bring your vision of an AI Sales Call Analyzer to life!

@PythonProHemant

Hi, I can build this system end-to-end using Python with a clean and scalable architecture. For the transcription layer, I would use Deepgram for fast and structured speech-to-text (with timestamps and speaker detection), and then use OpenAI for summarisation and extracting key insights like customer interest, sentiment, objections, and next steps. This combination works very well for turning raw calls into actionable insights. The backend will be built using FastAPI, with MongoDB for storing transcripts, summaries, and structured outputs. I’ll also create a simple dashboard where your team can upload calls, view timestamped transcripts, see summarized insights, and export the data as JSON when needed. I’ve built similar systems before including a voice bot receptionist for a medical company that handled real-time conversations, processed speech, and extracted structured information. So this workflow is quite familiar to me. I can deliver a working MVP within about a week. Let me know and I can get started. Thanks

@teerthofficial

Hello there, I have carefully reviewed your project details and fully understand your requirements. I’m confident in my ability to deliver high-quality results and would be glad to work with you on this. Looking forward to your response. Best regards, Thanks.

@maxakash1999

Hi, This project honestly feels very close to what I’ve been building recently, so I’d love to take this on. I’ve been working a lot on AI-driven conversation systems—especially around audio, real-time processing, and extracting meaningful insights from human interactions. Recently, I built a system where we stream audio, convert it to text, and then use AI to generate structured outputs like summaries, intent detection, and decision signals. So the flow you’re describing (audio → transcript → insights → dashboard) is something I’m very comfortable with. What I find interesting in your requirement is not just transcription, but the “what actually matters” layer—things like: when the customer shows real interest where hesitation or objections come in and what concrete next steps were agreed That’s exactly where I’d focus—using an LLM to structure the conversation into something your sales team can scan in seconds instead of listening to a full call. On the frontend side, I’ve built React dashboards that go beyond raw data—clean UI with highlights, sections, and quick summaries so users don’t feel overwhelmed. I’d keep this simple but useful: transcript with timestamps, a summary block, and clearly extracted action items. From a delivery standpoint, I can get you a working MVP in about a week, where you can upload a call and immediately see transcript + insights in a usable dashboard.

@netclickgr

You need a system that converts sales call recordings into actionable insights—transcribing audio, extracting sentiment and interest signals, identifying next steps, then presenting it all through a dashboard with visual scanning and structured export capabilities. I'll wire Node.js with Whisper for transcription, chain to Gemini or GPT for sentiment analysis and action item extraction, store results in MongoDB, and build a React dashboard displaying timestamped transcripts and auto-generated summaries. The full pipeline will handle MP3/WAV uploads and deliver insights in under 60 seconds per call. I've built similar Whisper-based analytics pipelines integrating AI summarization with browser dashboards for multiple clients. My bid is ₹12,500 INR with 4-day delivery. Ready to start—let's discuss your requirements.

@devcore123

This is a very strong and practical use case — turning raw sales calls into actionable insights is exactly where AI adds real business value. I can build an end-to-end system that: • Accepts audio uploads (MP3/WAV) via a Node.js backend • Uses Whisper API (or similar) for fast and reliable transcription • Applies an LLM-based analysis layer to extract: – Customer sentiment & interest signals – Key objections or hesitation points – Clear next steps and action items • Stores structured results in MongoDB • Displays everything in a clean React dashboard (timeline + summary view + export option) I would structure the system using: Node.js (Express), MongoDB, React, Redis (for background job processing), and OpenAI/Gemini APIs. ✅ MVP Deliverables: Upload + timestamped transcript AI-generated summary (sentiment + next steps) Simple dashboard for quick review JSON export endpoint ⏱️ Estimated timeline: 5–7 days for a working MVP I’ve worked with similar pipelines involving APIs, backend systems, and AI processing, so this is very doable with clean architecture and scalability in mind. If you'd like, I can also extend this later into lead scoring or sales performance analytics. Let’s discuss your priorities and I’ll start immediately. Best regards, dev-core

@presleyn6

As an experienced Freelancer in the field of software architecture, my skill set will bring value to your AI sales call analyzer project. While my focus has been primarily on Python/Selenium, I believe in the power of staying open to new technologies, so branching out into a Node.js Whisper backend isn't a problem. Combining Whisper with MongoDB and a clean browser-based dashboard? Your vision aligns perfectly with my capabilities. Throughout my career, I've developed numerous automation tools and systems that streamline processes. Taking raw audio files, utilizing speech-to-text API like Whisper for transcription, and then utilizing advanced NLP algorithms for semantic summarization and identification of critical segments is something I've successfully done before. And the results are not displayed in raw JSON format but rather a user-friendly layout. Additionally, I understand the real-world complexities of projects like these and always strive to deliver a Minimum Viable Product within a reasonable timeline. However, while timing is essential, quality is not compromised; you can expect a highly functional, easy-to-use system from me. Let's discuss further how I can articulate your needs with structured JSON along with a functioning visual dashboard to empower your sales team better and transform their approach with customers.

@jazzyhuang

Hey — read through your post on ai sales call analyzer. I've done similar work with PHP, JavaScript, Software Architecture recently. I can get a working version to you in about 1 week. What's the most important piece you'd want to see first? — Jazzy

@Amarpratap89

I will build a Node.js system that transcribes sales calls, analyzes sentiment and customer interest, extracts key action items, and displays everything in a clean dashboard with structured data export support.

@satyaevolfast

Hello, I understand you're looking to automate the analysis of recorded sales calls to boost team learning. For this project, I propose a Node.js backend to handle audio uploads (MP3, WAV), utilizing the Whisper API for speech-to-text conversion. Following transcription, I will implement a summarization layer that identifies key segments reflecting customer interest, sentiment, and agreed action items. The results will be stored in MongoDB, allowing for a streamlined dashboard that presents timestamped transcripts and autogenerated summaries. The UI will be designed for quick scans, complemented by an export functionality for future use. To ensure a smooth workflow, I will leverage existing libraries for audio processing and data visualization to expedite development. My experience with Node.js and natural language processing makes me well-suited for this project. If the scope expands, my team at ASPL can provide scalable support. I look forward to discussing the final details, timeline, and any specific libraries you have in mind. Best regards, Satya.

@fabianofff

Hi, I noticed you need a system that takes recorded sales calls, transcribes them, and surfaces the key insights — sentiment, buyer interest, and action items. That's exactly what I build. My approach for your project: 1. Node.js backend with file upload endpoint for MP3/WAV files 2. OpenAI Whisper API for accurate speech-to-text transcription 3. GPT-4o summarization layer to extract sentiment analysis, customer interest signals, hesitation flags, and concrete next steps 4. MongoDB storage for all transcripts and analysis results 5. Clean React dashboard for your reps to quickly scan call summaries, with JSON export I've built similar audio processing pipelines with AI analysis layers — the transcription + summarization chain is something I have production experience with. I'd use Whisper for transcription accuracy and GPT-4o for the intelligence layer since it handles nuanced sales conversation context better than rule-based approaches. I can deliver a working MVP in 10 days. Happy to walk you through the architecture in more detail.