Budget: 50 USD Deadline: 2 days

Hello, Ruslan!

We are assembling exactly such AI lead generation systems — n8n as the orchestrator, Google Sheets as a lightweight CRM, and an LLM agent (OpenAI) with dialogue memory that conducts conversations like a live realtor, not like a bot.

For Stage 1, I will provide at least two architecture options, and for each, I will outline: services and workflow, pros and cons, scaling for 100 / 1,000 / 10,000 contacts, operating costs, and risks — WhatsApp blocking, API limits, loss of context, message duplication, desynchronization with Sheets.

To be honest about WhatsApp Business API: the official channel is paid and works only through a BSP provider (Meta Cloud API or partner), which affects both the price and the limits. In the options, I will show both it and alternatives with justification, so you can choose based on numbers, not blindly.

One question to better design the dialogue memory: do we keep the conversation context within the same Google Sheets (the "last message" field plus auxiliary) or do we set up a separate storage for long dialogues with 10,000 contacts? This affects the choice of architecture and cost.

I am ready to show a live demo of our agent so you can see what a natural dialogue with memory looks like. I am taking Stage 1 at the starting price — I am gathering initial reviews on Freelancehunt, so I am making it advantageous.

Petr Pankov, BotCraft Group Expand

Budget: 55 USD Deadline: 4 days

Hello!
Thank you for the detailed and well-structured project brief — it’s clear that there is a thoughtful business logic behind it, rather than just a list of tools. This is exactly the type of project where it’s interesting to propose an architecture rather than just assembling a workflow based on a template.
Briefly about my relevant experience: I build AI automations on n8n using OpenAI Agent, including scenarios with dialogue memory, negotiation stage identification, and synchronization with CRM on Google Sheets — for example, a lead qualification system based on the BANT methodology with an AI agent that conducts the dialogue, analyzes the client's intent, and updates the status in the CRM after each message, as well as a voice AI agent with objection handling logic and edge cases, which is directly related to the requirement of "not looking like a bot."
I want to highlight an important architectural nuance regarding the WhatsApp Business API: initiating a conversation with a new contact can only be done through pre-approved Meta message templates — this is a limitation of the platform itself, not n8n. This directly affects the implementation of the requirement "not to look like a bot" in the first message, and I will definitely address this in the comparison of architectural options along with possible ways to mitigate this limitation.
I am ready to prepare two architectural options with a description of the workflow, pros/cons, scalability (100 / 1,000 / 10,000 contacts), operating costs, and risks — as specified in the brief.
The cost of the architectural phase: $55 (fixed amount).
I am ready to start work on Monday, July 20, and provide both architectural options within 3-4 working days.
I am available to answer any clarifying questions and discuss details in chat or on a call.
Best regards,
Elena Tudos

Budget: 150 USD Deadline: 3 days

Hello, Ruslan!

The task is clear: we need not just a connection between n8n and WhatsApp, but a managed system where AI conducts the dialogue considering the object's data and the history of correspondence, while the manager connects at the right moment.

I will prepare an architectural solution in two options:

1.
Quick MVP — Google Sheets + n8n + official WhatsApp Business API + OpenAI. Suitable for launching a pilot and a limited number of active dialogues.

2.
Scalable option — n8n + WhatsApp API + OpenAI + PostgreSQL for storing the history of correspondence, memory, queues, protection against duplicates, and error logs. Google Sheets will remain a convenient CRM interface for managers.

For each option, you will receive:

a diagram of services and workflow;

the logic of dialogue memory and CRM updates;

rules for transferring the prepared lead to the manager;

advantages, limitations, and risks;

an assessment of scalability for 100 / 1,000 / 10,000 contacts;

an estimate of external costs and a plan for launching the MVP.

I will separately consider the risks of WhatsApp: message duplicates, API limitations, number blocking, and requirements for the first contact. For Kazakhstan, it will be necessary to check the readiness of the WhatsApp Business Account/API and the acceptable communication scenario with the owners before launch. Expand

Budget: 50 USD Deadline: 2 days

Hello!
I see that you need not just WhatsApp automation, but a well-thought-out AI system that will conduct natural dialogue, remember the context of communication, and pass on a "warmed-up" owner to the manager. The architecture here determines how stably the system will operate when scaling.

I specialize in building AI automations based on Make.com, OpenAI, CRM, and AI agents for automating communication and lead generation. For this project, I can offer at least two architecture options: a classic one (Google Sheets + n8n + WhatsApp Business API) and a more scalable one with a separate AI memory storage, which will ensure quality continuation of dialogues even after a few days.

I will also detail the workflow, assess the risks (WhatsApp blocking, message duplicates, synchronization, API limitations), operational costs, and scalability for 100, 1,000, and 10,000 contacts.

Please let me know if you plan to use the official WhatsApp Business API through Meta/360dialog or if you are open to considering alternative BSP providers to reduce costs and simplify integration?

Budget: 120 USD Deadline: 3 days

Ruslan, for stage 1, I will prepare two comparable architecture options, rather than a general scheme:

1) official WhatsApp Cloud API + n8n + OpenAI + Google Sheets with a separate state and audit storage;
2) BSP (for example, 360dialog/Twilio) + n8n, with the same domain workflow and an option to transfer state from Sheets to SQL as load increases.

For each option, I will describe the services, sequence/workflow, data and memory model, dialogue stages and handoff to the manager, idempotency/retry/deduplication, operating costs for 100 / 1,000 / 10,000 contacts, as well as risks of opt-in/templates, 24-hour window, WhatsApp quality limits, context loss, and CRM desynchronization. The result will be a document with diagrams, a comparative table, recommendations, and a plan for the next stage.

There is a self-initiated demo of a secure n8n/OpenAI workflow with an approval gate and a separate live API/CRM demo; I do not attach an exact production case for WhatsApp:
https://prooflab-live-cases.dolponik.chatgpt.site/demos/automation

Before starting, I will clarify: is the WhatsApp Business already verified and how many new owners/active dialogues are expected per month? Expand

Budget: 4000 USD Deadline: 4 days

Good day! I design and use AI automation daily (n8n-like pipelines, LLM agents with context memory, integrations with CRM/spreadsheets/messengers for my own e-commerce). Your specifications are well-written, and I will immediately point out two pitfalls that I will incorporate into the architecture: (1) WhatsApp Business API allows initiating a dialogue only with approved templates and has a "24-hour window" rule — this directly affects the first contact scenario and the risk of blocking; (2) the "memory" of the dialogue when sending a message again after days — is a separate layer of state storage outside of n8n, otherwise the context is lost. I will create 2-3 architecture options exactly according to your structure: services, workflow, pros/cons, scalability for 100/1k/10k contacts, operating costs for each service, risks, and how to mitigate them. I will separately compare WhatsApp API with alternatives and explain when each is appropriate. Please clarify: do you already have a verified WhatsApp Business account, and how many new owners do you expect per month? This affects the choice of tariffs and architecture.

Budget: 77 USD Deadline: 3 days

An interesting project at the intersection of n8n, CRM logic, and AI dialogues. I understood the essence: it's not just a survey bot, but a realtor with memory that conducts dialogues in stages and does not ask for known data (area, price, residential complex). I will prepare at least two architecture options (for example, WhatsApp Business API through a provider vs alternatives like Baileys/Green API with pros and cons), outline the workflow in n8n, synchronization with Google Sheets, risks (blocks, message duplicates, loss of context), and scalability from 100 to 10,000 contacts. I am ready to present the document in about 3 days.

Budget: 87 USD Deadline: 3 days

The official WhatsApp Business API is already connected, or should I compare it with the alternative (Evolution API/Baileys) in terms of price and risks of blocking? I will offer two architecture options on n8n with Google Sheets as CRM: with dialogue memory, AI stages, and scaling up to 10,000 contacts. Ready in 3 days.

Budget: 50 USD Deadline: 1 day

Good day, I am ready to complete your task quickly and efficiently. I have extensive experience in creating various bots. Please write to me in private messages to discuss the details. I will be happy to help :)

Budget: 15000 USD Deadline: 5 days

A system is needed where n8n automatically detects a new owner in Sheets, messages them on WhatsApp, and conducts a dialogue like a realtor, not a bot — with memory, without repeated questions about the property.

I will propose two architecture options. The first: n8n polling Sheets every 5 minutes, a trigger on a new row, sending via the official WhatsApp Business API (360dialog or Twilio), context memory through a separate Sheets tab or a simple vector store in Supabase, OpenAI for generating responses with a realtor system prompt. The second: webhook trigger from Sheets via Apps Script, n8n as the orchestrator, memory through Redis/Upstash (faster and more reliable with 1000+ contacts), the same OpenAI Agent with tool-calling for CRM updates.

A key risk that is important to incorporate into the architecture from the start: deduplication of messages during repeated triggers and idempotent updates of rows in Sheets; otherwise, duplicates and status desynchronization will occur under load.

How many simultaneous active dialogues are expected at the start, and is there already a connected WhatsApp Business API account?

Budget: 125 USD Deadline: 2 days

Hello! I have extensive experience in designing automated systems based on n8n and integrating LLM (OpenAI) with CRM systems. I am ready to prepare a detailed technical solution for you that will ensure a "human-like" dialogue, correct context handling, and seamless synchronization with Google Sheets. As part of the proposal, I will outline two architecture options: one using the official WhatsApp Business API and the other with alternative solutions to optimize costs and reduce the risk of blocks. I will take into account all your requirements for scalability and the logic of the AI agent's operation. I am ready to start the analysis and prepare the documentation. Write to me, and we will discuss the details.