AI automation of email responses (n8n / Make, RAG, multi-turn agent)

Budget: 500 EUR Deadline: 15 days

Dariya, good day!

I have 3+ years of experience working with agentic workflows (multi-turn agents, memory, state) and n8n/Make, Airtable, OpenAI/Claude API. I am ready to implement AI automation for email responses: classification of emails from Outlook, RAG from Airtable, autonomous responses with context, guardrails, and integration with the calendar.

Can we discuss the details?

Budget: 499 EUR Deadline: 13 days

I have created RAG agents of various types and have experience building autonomous systems specifically for email, so the project is very clear to me. I will set up the architecture in n8n or Make (your choice), which will provide the agent with "memory" and context through Airtable.

Why I am confident in the result:

Experience with RAG: I know how to structure a knowledge base in Airtable so that the agent provides medically accurate responses based solely on your content.

Working with email and entities: I have already implemented scenarios with Outlook/Gmail, where the system automatically extracts products, volumes, and order parameters from the body of the email.

Flexibility in the stack: I work freely with OpenAI/Claude API. Regarding CRM — I have experience with KommoCRM and can easily integrate your system into the overall workflow.

Security (Guardrails): I will definitely implement a Sentiment-check and a "Drafts" system so that at the initial stage you can control the agent's responses before sending.

The project is very interesting, and I am ready to discuss the details and architecture in private messages. Expand

Budget: 750 EUR Deadline: 7 days

Good day.
I am ready to take your project into work.
I have already developed similar AI agents using low-code tools.
I can develop one for you as well.
Write to me privately, we will discuss all the details and choose the best solution for you.

Budget: 1300 EUR Deadline: 7 days

Hello! I have carefully studied the task. I am ready to implement a full-fledged Multi-turn Agent with context retention, as one-off responses will be ineffective for medical sales and may carry reputational risks.

My approach to implementation (Architecture & Stack):

Orchestration (n8n): I use n8n (Self-hosted/Cloud) as the main core. This allows for flexible management of logic without the limitations of Make.

Memory & Context (Stateful):

I will implement the storage of conversation history (Threads) in Airtable.

The session key will be Message-ID / Sender Email. The agent will "read" the past 3-5 messages before generating a response to maintain the thread of the conversation.

RAG (Knowledge Base):

Vectorization of the knowledge base (OpenAI Embeddings) for accurate answer retrieval regarding the price list and services, to eliminate hallucinations.

Guardrails & Safety:

I will implement an intermediate node for Sentiment Analysis.

Logic: If the email is negative or contains trigger words ("complaint," "bad," "urgent") — the AI will not respond itself but will create a ticket for the manager with the note 🔴 Human Help Needed.

Integrations:

Outlook (Graph API / IMAP) for monitoring.

Webhooks for communication with external CRM (if needed in the future).

Why you should work with me: I am a developer specializing in complex automation scenarios. My profile is not just about "setting up blocks," but building a fault-tolerant architecture (Error Handling, retries on API failures, data validation).

I am ready to discuss the details by voice and show examples of the logic. When would it be convenient for you to have a call? Expand

Budget: 800 EUR Deadline: 21 days

Dariya, hello 👋

Ready to dive into the complex variant — **multi-turn email agent with memory, RAG, and guardrails**, rather than a one-off reply.

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## 🔧 Technical Approach (solution architecture)

**System flow:**

Outlook → n8n/Make (orchestration) →
LLM (classification + entity extraction) →
RAG (Airtable KB) →
Response generation →
Guardrail validation →
Send / Human handoff →
Thread memory update (Airtable)

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## 🧠 Stack

**Orchestration:** n8n or Make
**LLM:** OpenAI (GPT-4o/4.1) or Claude
**Memory + RAG:** Airtable
**Optional:** CRM (HubSpot / Pipedrive)

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## 📌 What will be implemented

* Classification of emails (sales / support / spam)
* Entity extraction (product, quantity, parameters)
* RAG with migration from Excel → Airtable
* Multi-turn memory (thread logging + summary window)
* Automatic response generation
* Guardrails:

* sentiment-check
* stop-logic for complaints
* fallback on API failures
* confidence threshold + human handoff

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## ⚠️ Risks and how to mitigate them

* Hallucinations → strict RAG + secondary LLM validation
* Context drift → structured memory + thread summarization
* Token cost → model separation (cheap for classification, strong for generation)
* GDPR (DE, medical niche) → minimization of PII + data storage control

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## ⏱ Timeline

MVP (multi-turn without complex CRM logic): **10–14 days**
Full production-ready system: **3–4 weeks**

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## 💶 Budget

MVP: **600–800 EUR**
Full system: **1000–1300 EUR**

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I can start as early as next week.
If convenient, I will prepare a short architectural diagram with a breakdown by modules before starting, to fix the scope and avoid task ambiguity. Expand

Budget: 1000 EUR Deadline: 30 days

Good day, Daria!
I have practical experience in building e-mail AI agents with memory and dialogue logic: the bot analyzes incoming emails, understands the request, refers to the knowledge base, formulates a response, and maintains the history of correspondence without losing context. I work with n8n, connected Outlook, OpenAI / Claude, Airtable as a knowledge base and storage for correspondence.

I create not separate scenarios, but a complete coherent system with checks, stop logic, and error handling.
You can view the completed projects in the portfolio Freelancehunt

Budget: 100 EUR Deadline: 1 day

I am among the top 5 developers in the category of "Artificial Intelligence and Machine Learning" among ~2100 specialists on the platform.
I guarantee:
- Fast and high-quality task execution
- Strict adherence to deadlines
- Regular communication throughout the entire process
I would be happy to discuss the details of your project in private messages.

Budget: 550 EUR Deadline: 15 days

Dariya, good day!

I have over 3 years of experience working with agentic workflows — I develop autonomous multi-turn agents with memory (thread logging, state management), contextual RAG, and clearly defined guardrails.

I work with the stack:

n8n / Make — orchestration of scenarios, webhooks, API integrations
Airtable — knowledge base, memory store, logging thread context
OpenAI / Claude API — classification, entity extraction, response generation
Outlook API — processing inbound emails and automatically sending replies

For your project, I propose to immediately implement a more complex scenario — an autonomous multi-turn email agent that:

* analyzes and classifies incoming emails (request / support / order / spam)
* extracts entities (products, quantity, parameters)
* uses RAG from the knowledge base in Airtable (with migration from Excel)
* generates relevant responses considering the history of correspondence
* stores the thread context in memory tables
* automatically adds a consultation link in Outlook when there is a corresponding intent
* has guardrails: sentiment-check, stop logic for complaints, fallback for API failures

I also have experience with CRM integrations (HubSpot, Pipedrive) and building end-to-end automations, not just individual scenarios.

I am ready to start as early as next week and implement the solution modularly or completely turnkey.

I would be happy to discuss the details. Expand

Budget: 200 EUR Deadline: 3 days

Hello! I have reviewed your project and am ready to start working. I can guarantee excellent results in a short time.

Budget: 1500 EUR Deadline: 10 days

Hi Dariya
I hope you are doing well.
I have hands-on experience building agentic email automation with multi-turn logic, memory, and guardrails using n8n / Make, Airtable, and OpenAI / Claude APIs. I’ve implemented workflows that classify inbound emails, extract entities, retrieve context via RAG, store thread memory, and autonomously generate replies with sentiment checks, stop-logic, and fallback handling.

Comfortable with Outlook integrations, API/webhooks, modular delivery, and end-to-end automation design. I can start within a week and scale this into further projects if needed.

Best,
Tobias

Budget: 1000 EUR Deadline: 7 days

Hello,

I’ve built and deployed agentic email and CRM automations where AI handles multi-turn conversations with memory, state, and guardrails—not just single replies. Typical setups include email ingestion (Outlook/Gmail), LLM-based classification and entity extraction, RAG over Airtable/Notion/SQL knowledge bases, and autonomous response generation with stop logic for complaints, sentiment checks, and human handoff.

My go-to stack aligns well with yours: n8n and Make for orchestration, Airtable as lightweight memory/KB, and OpenAI / Claude APIs for reasoning and generation. I’m comfortable designing end-to-end systems—thread logging, error handling, API fallbacks, and CRM syncs (HubSpot, Pipedrive)—so the automation is reliable in production, not just impressive in demos.

Happy to start with a focused module and scale into a fully autonomous inbound sales agent if the first phase performs well.

Best regards,
Jeo

Budget: 1000 EUR Deadline: 3 days

Good day!
I have experience in developing agentic workflows (multi-turn, state, memory) for email automation. I confidently work with n8n/Make, OpenAI/Claude API, and Airtable for RAG, context, and guardrails. I am ready to start next week.

Message me privately, and we will clarify the details.