Multilingual AI IVR and ERPNext Integration

@kamran2012

Hi there, I will build your multilingual IVR system with Sarvam AI integration, the custom Frappe app — Doctypes, whitelisted API endpoints, scheduler jobs — and the full ERPNext pipeline connecting Bitla GDS, GPS telematics, and WhatsApp Business API. For the bridge call logic, I will implement a time-window guard that checks the passenger's boarding time against the live GPS ETA before opening the masked connection — this prevents premature driver calls while still accounting for early arrivals when the vehicle is ahead of schedule. Questions: 1) Are you deploying on Bolna or Exotel, or do you need a recommendation based on regional carrier reliability? 2) For the OCC WhatsApp loop, should ticket escalation trigger if no "DONE" reply arrives within a configurable SLA window? Looking forward to talking through the details. Kamran

@mubeenm5026

As an experienced and versatile developer specializing in AI, Python, Node.js, and Android, I am confident that I can meet and exceed the requirements of your project. My company, Web Crest is renowned for building innovative and efficient AI solutions for clients across multiple industries. Not only do we have the technical expertise you require to develop a comprehensive-multilingual IVR system integrated with your ERPNext instance through Bolt API and WhatsApp Business API, but we also understand how to align technology with your business needs. For instance, having developed AI chatbots before, I'm knowledgeable about Sarvam's ASR/NLU/TTS technology which will be fundamental in realizing the multilingual aspects of the project in Tamil, Telugu, Kannada, Malayalam, and English. Complementing this proficiency in language processing is my expertise in-building self-service features such as vehicle ETA, boarding point info retrieval, driver details(authorized masked bridge call) etc - all while ensuring driver privacy by restricting direct access to driver number more than 15 minutes prior to boarding time.

@Hrolgar

For an intercity bus IVR in South Indian languages, the first design decision is whether to detect the caller's language automatically or let them self-select at the first prompt. It sounds minor, but it cascades into ASR engine choice, the LLM prompt structure, and how you map caller state to ERPNext session context. Worth agreeing on before anything gets built. The integration spine I'd use: Asterisk or Plivo handles the call layer, a regional ASR engine (Sarvam AI or Bhashini, both have solid Tamil/Telugu/Kannada/Malayalam coverage) handles recognition, and a Python/Node service in the middle orchestrates the dialog and hits ERPNext's REST API for booking reads and schedule lookups. The ERPNext sync needs idempotent booking writes keyed to a unique call reference so redialed or dropped calls don't create duplicate records. This is an indicative estimate from the brief; I'll give you a firm quote once the scope is locked. M1: Call layer setup (Asterisk/Plivo) + ERPNext API skeleton + language selection flow, 37,500 INR, 5 days. M2: ASR/TTS integration for two languages minimum, extensible to the full set, 37,500 INR, 5 days. M3: Booking and schedule dialog flows with idempotent ERPNext sync, 37,500 INR, 6 days. M4: Remaining language support, operations queries (cancellations, trip status), testing and handover docs, 37,500 INR, 5 days. Which South Indian languages are in scope for launch, and is there an existing ERPNext instance with live booking data I can map against, or are I starting from a fresh setup?

@techsty2014

Hi, We will build your multilingual IVR system with Sarvam AI (ASR, NLU, TTS) and integrate it into ERPNext via a custom Frappe app: Doctypes, whitelisted endpoints, and scheduler jobs included. For the IVR flow, we will route each call through language detection first, then match the caller's mobile number against ERPNext before falling back to voice PNR entry. Bridge calls to drivers will be gated by a 15-minute boarding window check against your GPS telematics feed. A couple of quick things to confirm: 1) Is your Bitla GDS API already accessible, or do we need to coordinate access with them? 2) Are you leaning toward Bolna or Exotel for telephony, or should we evaluate both? The number quoted here is a starting estimate. Send me a message and we can go over the details. Best regards, Faizan

@himanshus642

Hi, I am an experienced full-stack developer with regular hands-on work in AI voice agents, IVR systems, WhatsApp automation, ERPNext, and custom Frappe applications. I have worked on similar automation and business workflow systems using tools such as Sarvam AI, Bolna, Exotel, WhatsApp Business API, and API-based integrations. For your intercity bus service use case, I can help build a reliable AI IVR and OCC ticketing flow, including call automation, customer query handling, WhatsApp follow-ups, GPS/API integration, and backend workflow management. I also have strong experience with ERPNext and Frappe, including custom Doctypes, server scripts, API endpoints, scheduler jobs, background workers, permissions, and business-specific modules. A key advantage is that I also manage and distribute Frappe/ERPNext applications on my own server infrastructure, so I understand both development and deployment at a production level. This helps ensure the system is not only built properly but also deployed, maintained, and scaled reliably. My approach is milestone-based, with clear communication, proper testing, and business-focused execution. I would be happy to discuss how we can implement a complete AI IVR + Frappe-based workflow solution for your operations.

@abhishek060

Hi, I’ve reviewed your requirement along with the attached flow details for the IVR + ERPNext integration. The scope is clear and quite well-structured for a full-scale operational automation system. I can build this end-to-end—multilingual AI IVR using Sarvam AI, ERPNext custom app with required Doctypes and APIs, real-time GPS + Bitla integration, and a WhatsApp-based ops loop for ticket handling and passenger notifications. The driver masking + time-based bridge call logic and automated delay/cancellation workflows are also fully doable. Before I finalize the approach, I just need a few specifics to align everything correctly: For IVR traffic, what is your expected daily call volume and peak concurrent calls? Are you already using a WhatsApp Business API provider (like Gupshup/Interakt/Meta Cloud) or should that be set up from scratch? For GPS tracking, which telematics provider are you using (or is it custom feed from buses)? Do you want ERPNext to include a live operations dashboard (map + trip status + active alerts) for your control room team? Once I have this, I can map the exact architecture, SLA rules, and deployment plan for a production-grade rollout.