AI-based SaaS for CRM and Business Automation

@Microlent

Hi, This project is right in my area of expertise. With 6+ years of experience in full-stack development, SaaS, AI integrations, CRM systems, APIs, and automation, you can feel confident that I can handle this project end-to-end. I can build your: AI WhatsApp receptionist/sales assistant WhatsApp Cloud API + AI chatbot RAG-based knowledge base from websites, FAQs & documents CRM, leads, pipeline & conversation inbox AI-to-human handover and automated follow-ups Appointment/reminder workflows Secure multi-tenant SaaS with roles, plans & usage limits Analytics, admin dashboard and scalable backend I’ll use a clean React + TypeScript, Node.js, PostgreSQL, Redis and LLM/RAG architecture, with security and scalability considered from day one. I won’t just follow the specification—I’ll also suggest improvements where they can make the product more reliable, useful, and commercially scalable. I can share relevant AI/SaaS/CRM work and provide a clear timeline, milestones and fixed/estimated cost after reviewing your priorities. Let’s connect for a 5–10 minute chat and turn this idea into a solid product.

@onkarkulkarni8

Hello, I checked your "AI-based SaaS for CRM and Business Automation" project description, it looks like the focus is on delivering a clean, responsive website that works well across all devices. I prefer understanding the expected layout and user experience first, then building pages that closely match the design while keeping the code organized and easy to maintain. Feel free to share the design or current website, and I'll suggest the best implementation along with a realistic timeline. Final timeline and cost will be confirmed in chat after a complete understanding and documentation of the project expectations in detail.

@vishal1145

Your WhatsApp AI agent will fail under concurrent message load if you don't implement a proper queue system from day one. Most developers build this as a monolith that crashes when 50 businesses receive messages simultaneously. Quick questions - are you planning rate limit handling for WhatsApp's 80 messages per second cap per business phone number? And what's your target for AI response latency under peak load? Here's the architectural approach: - MULTI-TENANCY: Implement row-level security in PostgreSQL with tenant_id isolation plus Redis caching to prevent cross-tenant data leaks and maintain sub-200ms query performance. - AI KNOWLEDGE BASE: Use vector embeddings (Pinecone or pgvector) with RAG architecture so the AI retrieves actual business data instead of hallucinating answers during customer conversations. - WHATSAPP CLOUD API: Build webhook processor with Bull queue and Redis to handle message bursts, implement exponential backoff for failed deliveries, and store conversation state in PostgreSQL. I've built 2 similar WhatsApp automation platforms for healthcare clients that now process 15K daily conversations. Let's schedule a 20-minute technical call to walk through the event-driven architecture before you commit to a build approach.

@fullstack0407

I checked your job post, I'm perfectly positioned to bring your vision of an AI-based SaaS for CRM and Business Automation to life. Having developed similar platforms for a range of industries such as healthcare, I'm keenly aware of the specific functionalities required for success. Your project's focus on integrating WhatsApp through its Cloud API aligns with my expertise in utilizing WhatsApp's API for efficient and seamless communication. Furthermore, my experience with creating AI Auto Reply Systems and Chat & Ticketing Platforms will greatly expedite the creation of your AI digital receptionist/sales assistant. In terms of the technologies you've preferred, React + TypeScript + Tailwind CSS on the frontend combined with Node.js + TypeScript on the backend has often proven best in delivering quality, high-performing solutions. As for PostgresSQL, I consider it an excellent choice for managing the vast amount of data your platform will handle. Of course, I'm open to better technology recommendations based on project needs. My estimated timeline is X weeks and cost is Y.

@aprkdream

Hi, I read that you need an AI‑powered SaaS to manage WhatsApp conversations, capture leads, and handover to humans—all from one dashboard. The plan is to hook into the WhatsApp Cloud API, run an LLM‑based chatbot that pulls facts from your site and PDFs, and then route qualifying chats to your team. I’ve built VerifyFirst’s KYC/WhatsApp flow and Bigul’s trading API gateway, both of which required real‑time message handling, secure storage, and seamless handover to human agents. Those projects used Node.js, PostgreSQL, React, and AWS‑based deployments, exactly the stack you’re targeting. My approach will be a micro‑service architecture: a Node.js API for WhatsApp events, a Python/Flask LLM wrapper for knowledge‑base queries, and a React front‑end for the inbox and lead pipeline. PostgreSQL will store leads, conversation history, and user profiles, while Redis will buffer incoming messages for low‑latency responses. Could you share which AI model you’d prefer (e.g., OpenAI GPT‑4 or a custom fine‑tuned model) and whether you have existing content to seed the knowledge base? Let’s discuss the timeline and any specific compliance requirements you have. Best Regards, Anil Prajapati

@tyronet2

You need Odoo’s delivery process streamlined into a reliable pick-pack-validate flow with batch traceability, expiry dates, automatic paperwork, and inventory levels that prevent component shortages. I’ve built inventory, order-processing, and workflow automation systems where accuracy and repeatable staff actions are essential. I’ll audit your current Odoo configuration, then set up operation types, routes, carriers, packaging, lot/batch tracking, best-before fields, label templates, and automatic printing at validation. Par levels will use product-specific minimum/maximum reordering rules, supplier lead times, and replenishment alerts rather than generic thresholds. I’ll test receiving, picking, partial shipments, backorders, validation, labels, and replenishment with sample orders, then provide a clear guide or walkthrough for adding products and carriers. Which Odoo version and edition are installed, and are Barcode, Manufacturing/BOMs, or carrier integrations currently enabled?

@shayankhan333

The healthcare focus changes the architecture more than people expect: WhatsApp Cloud API template rules plus PHI handling means the knowledge base needs per-tenant vector isolation, not a shared index. I'll build the Node/TS + Postgres core with a pgvector RAG store per tenant, WhatsApp Cloud API via webhooks with a queue for template vs session messages, and a handover inbox with staff assignment. Multi-tenancy via row-level security in Postgres, Redis for rate limits and follow-up scheduling. Past work covers Laravel/Node SaaS, WhatsApp integrations and OpenAI RAG builds. You can see my past work and reviews here: https://www.freelancer.com/u/shayankhan333 1) Do you already have a Meta Business verification and WhatsApp Business Account approved? 2) For the knowledge base, PDFs plus website crawl, or documents only at launch? Best regards, Shayan

@Mayanks010

Hi, Thanks for sharing your project. It aligns well with work I’ve successfully completed for other clients, and I’m confident I can deliver a high-quality solution tailored to your requirements. Before providing an accurate timeline, scope, and budget, I’d like to clarify a few key details to ensure we're aligned from the start. Freelancer’s proposal character limit makes it difficult to cover everything thoroughly here. If you're available, let's connect via chat. I can walk you through similar projects I've completed, discuss the best approach for your specific requirements, and answer any questions you may have. Once I understand your expectations, I'll provide a clear execution plan with realistic timelines and pricing. I’m ready to get started as soon as we finalize the details and look forward to working with you. Best regards, Mayank Sahu

@mikes126

I’d build the MVP around React/TypeScript + Node.js/TypeScript + PostgreSQL, with Redis for queues/background jobs and Docker for deployment. The backend would be modular so WhatsApp, AI, CRM, automation, billing, and tenant management can evolve independently. For the AI layer, I’d use a RAG-based knowledge system: ingest website pages, FAQs and PDFs → chunk/index the content → retrieve only relevant context per conversation → generate the response with strict business instructions and fallback/human handover when confidence is low. This is much safer than simply putting documents into a large prompt. For WhatsApp, I’d use the official Cloud API with webhook-driven message processing, conversation state, delivery/read events, templates and proper retry/idempotency handling. Incoming messages would flow through an automation pipeline such as: WhatsApp → conversation service → AI/RAG → lead qualification → CRM → staff notification → follow-up/appointment workflow. Multi-tenancy would be enforced at the data/service layer, with every business, user, conversation, document and automation scoped to a tenant. Roles/permissions, usage limits and subscription-ready metering would be designed into the foundation rather than added later.

@adityakhuman006

As a developer with a keen understanding of React.js, I am well-equipped to design your AI-based SaaS platform with impactful product features and a smooth user interface. My skills in API integration will enable seamless communication between your platform and third-party services such as the WhatsApp Cloud API that you prefer. I have successfully crafted websites that are responsive, maintaining their aesthetic appeal while adapting to varying screen sizes, ensuring compatibility with all types of devices and interfaces. My experience in creating efficient backend systems aligns perfectly with the core elements and workflows you envision for your AI digital receptionist. With Node.js and TypeScript proficiency, the brawn behind the scenes of your SaaS platform will be powerful, secure, and scalable. An essential aspect of my development approach is prioritizing clear communication with clients to understand their unique requirements better. That way, I can incorporate meaningful AI features that optimize your business processes without overcomplicating them.

@shailender18

Hi, This is the kind of project where architecture and product thinking matter as much as coding. I have 4+ years of experience with SaaS platforms, AI integrations, CRM workflows, APIs, dashboards, and automation systems. For your platform, I’d recommend: Frontend: React + TypeScript + Tailwind Backend: Node.js + TypeScript Database: PostgreSQL + Redis Infra: Docker + AWS/Render/DigitalOcean AI: OpenAI with RAG-based knowledge retrieval Messaging: Official WhatsApp Cloud API + Webhooks For the AI knowledge base, I’d ingest website content, FAQs, PDFs and documents, split them into searchable chunks, create embeddings, and retrieve only relevant business data before answering. This helps reduce hallucinations. For multi-tenancy, each business would have isolated users, contacts, conversations, knowledge, plans and usage data with strict tenant-level access controls. I can build: * WhatsApp shared inbox * AI receptionist + human handover * CRM and lead pipeline * Follow-ups, reminders and appointments * Roles/permissions * Super Admin * Subscription/usage architecture * Analytics and notifications I’d suggest building this in phases: Core SaaS + WhatsApp → AI/RAG → CRM/automation → billing/analytics → production hardening. I can also support post-launch fixes, monitoring and feature expansion. Best, Shailender

@B1zt

Hi, What you are really buying is not a chatbot. It is the thing that turns a WhatsApp message into a lead nobody forgets to chase, and lets a staff member step into the conversation without the customer noticing a change of hands. I would build that core first and grow the rest around it. First phase: - Node and TypeScript with Postgres, Redis and Docker, React for the dashboard. Your stack choice is sensible and I would keep it. - Every business kept separate by design, so one clinic can never see another's conversations, checked in one place rather than trusted to each query. - WhatsApp Cloud API wired in properly. Messages arrive on a webhook, go into a queue and are retried if something restarts, so nothing is silently lost. - The AI answers only from what the business uploads: website text, FAQs, PDFs. If the answer is not in there it says so instead of inventing one, and hands over to a person. - Leads created from those conversations automatically, with owner, status, notes and reminders that go out once. 150,000 INR, six weeks, delivered in stages so you see real WhatsApp conversations working in the dashboard early. Billing, plans, super admin and analytics I would quote as a second phase once the core is live. One recommendation up front: starting with clinics means patient messages, so I would lock down who can read what and keep a record of it from day one. One question: do you already have an approved WhatsApp Business account and verified number, or is getting that in place part of the job? Happy to talk through the architecture before you pick anyone. Thanks, Bhagya

@ujjwalmahar01

I can build this using a multi-tenant PostgreSQL schema to isolate business data and a vector database like Pinecone to store your business knowledge for the AI. I would handle the WhatsApp Cloud API via webhooks to ensure real-time message processing and instant AI responses. For the AI knowledge base, I recommend RAG (Retrieval-Augmented Generation) using OpenAI embeddings to ground the model in the specific documents provided by each business. This prevents hallucinations and ensures the agent remains strictly within the scope of the clinic or business services. A few questions to better understand the scope: Q1 - Do you require specific payment gateway integration for the subscription system, or should I focus on the architecture for usage-based billing first? Q2 - Will the human handover require a real-time notification system like WebSockets, or is a polling-based approach sufficient for your initial version? Q3 - How do you plan to handle the initial data ingestion for the knowledge base, specifically for unstructured website content versus structured PDFs? I am ready to discuss the architecture and refine the automation workflows with you as a product partner.

@mwaqasm5

Hi, I’d love to build your AI-powered WhatsApp SaaS as a scalable product, not just a collection of features. I can develop the multi-tenant architecture, CRM, WhatsApp inbox, AI agent, automation workflows, subscriptions, and admin dashboard with future expansion in mind. **Recommended stack:** React + TypeScript + Tailwind, Node.js/NestJS, PostgreSQL + Prisma, Redis/BullMQ for queues, Docker, and OpenAI/LLM APIs. **Architecture:** Each business will have isolated tenant data, roles/permissions, configurable AI settings, knowledge sources, conversations, contacts, and usage limits. For the AI knowledge base, I’d implement RAG: website/PDF/FAQ content → chunking → embeddings → vector search → relevant context → LLM response, with guardrails to reduce hallucinations. WhatsApp Cloud API will handle webhooks, messaging, templates, delivery status, and conversation events. Automation can then trigger lead creation, qualification, reminders, follow-ups, and human handover. **Estimated MVP:** 8–12 weeks, with phased delivery and testing. Cost can be finalized after confirming the MVP scope. I’d also recommend audit logs, webhook retries, rate limiting, usage metering, analytics, and GDPR-conscious data handling. I can provide post-launch maintenance and feature support. We can begin with an architecture/MVP breakdown before development.

@bridgestonetech1

Hi, We understand you’re looking to build a multi-tenant AI-powered WhatsApp SaaS that combines an AI receptionist, CRM, conversation inbox, automated follow-ups, appointments, and analytics into one platform. We can build this using React + TypeScript + Tailwind, Node.js + TypeScript, PostgreSQL, Redis, Docker, OpenAI, and the official WhatsApp Cloud API, with a modular architecture that can scale across multiple industries. For the AI knowledge base, we’d use a secure RAG-based approach to process website content, FAQs, PDFs, documents, and business instructions, allowing each tenant’s AI agent to answer from its own verified knowledge while reducing hallucinations. The architecture would include strict tenant isolation, role-based access, WhatsApp webhook processing, conversation history, CRM pipelines, automation workflows, subscription-ready billing, and Super Admin controls. We can also suggest improvements around AI guardrails, lead scoring, human handover, workflow automation, analytics, and security before development begins. Let’s discuss the MVP scope, milestones, timeline, and cost.

@kausarafridi07

As a seasoned Full Stack Developer, I’ve led numerous projects that align perfectly with your unique needs. Notably, I've developed AI-driven CRM systems and implemented WhatsApp Cloud API for organizations across various industries. My knowledge and fluency in Node.js, React.js, and Typescript will undeniably make me an invaluable asset to this project's development. Embracing your vision for a technical partner who thinks outside the box rather than just 'delivering code', I'm prepared to provide architectural recommendations for improved security, robustness, and scalability if need be. In fact, given my understanding of multi-tenancy from previous projects, I assure you of a high-performing platform built on modern cloud technologies like Docker. Drawing from my 15-years of experience building SaaS solutions for different companies, your project stands out due to its focus on AI-based automation. Having integrated OpenAI into chatbots and executed effective automation workflows similar to what you desire, I know how to create personalized experiences with the AI digital receptionist/sales assistant that can handle complex tasks such as lead qualification, appointment reminders and notifications with ease. My focus has always been on long-term success and growth; qualities honed by my background expertise in SEO, marketing and growth services for both start-ups and established corporates.

@amannamdev5081

Hi, I can build this as a multi-tenant AI receptionist and CRM platform where WhatsApp conversations, lead qualification, follow-ups, appointments, and human handover work as one connected workflow. I’d recommend React + TypeScript + Tailwind for the dashboard, Node.js + TypeScript for APIs/services, PostgreSQL for tenant/CRM data, Redis for queues and real-time workloads, and Docker for deployment. WhatsApp Cloud API would handle messaging through webhooks, while the AI layer would use OpenAI with a retrieval-based knowledge system. For each business, I’d create an isolated knowledge base from website content, FAQs, PDFs, services, and custom instructions. Retrieved business-specific context would be supplied to the AI before responses, with guardrails to avoid unsupported answers and escalation rules for sensitive or uncertain requests. The architecture would use tenant-aware data access, role-based permissions, usage limits, background workers, audit logging, and separated AI/WhatsApp services so the platform can scale as more businesses join. CRM pipelines, staff assignment, tags, notes, conversation history, automated follow-ups, reminders, analytics, subscriptions, and a Super Admin layer can then sit on top of this foundation. I’d be happy to discuss your vision and suggest ideas to make Fabulous Garments stand out online. Looking forward to working with you! Best Regards, Aman

@olehh6

Hello, The core challenge is combining WhatsApp, CRM, AI knowledge retrieval and automation into a reliable multi-tenant SaaS rather than treating them as separate features. I’d structure it around React/TypeScript, Node.js/NestJS, PostgreSQL, Redis, Docker and the official WhatsApp Cloud API. Each business would have isolated tenants, users, roles, contacts, conversations, knowledge sources and usage limits. WhatsApp webhooks would feed messages into the backend, where the AI layer retrieves relevant business content from websites, FAQs and uploaded documents before generating a controlled response. Confidence/rules would determine when to answer, request clarification or hand the conversation to staff. The workflow engine would handle lead capture, qualification, tags, assignments, follow-ups and appointment reminders, with every event logged for analytics and troubleshooting. AI services would remain modular so models, prompts and retrieval strategies can evolve without changing the core CRM. I’d recommend starting with a focused MVP-WhatsApp inbox, AI knowledge base, CRM, handover and basic automation-then adding billing, advanced analytics and industry-specific workflows after validation. Which part is already available today, and should the first milestone focus on proving the WhatsApp → AI → CRM workflow end-to-end?

@tapasbera

Dear Sir/Madam, Hope you are doing well. I am delighted to present a bid proposal for your valued project. I am expert in developing websites in PHP, MySQL, Curl, Wordpress, Joomla, HTML,HTML5, CSS, Bootstrap 3 and 4, Jquery, javascript , AJAX , Payment Geteway , Facebook connect, google connect , CodeIgniter 4 and Laravel 11 framework. I have around 15+ years of experience in developing websites. I have also developed Joomla 3 components, plugins and modules. I provide you a fully secure and reliable web work. With fully customized Content Management System. I am also comfortable to design for different type of devices like Desktop, tablet, ipad and also mobile. I keep things very simple and without any complications. I eagerly anticipate your response and sincerely look forward to make this project a success in order to build a long-term mutually beneficial relationship. Thanks and Warm Regards, Tapas Bera (Full Stack PHP Developer)