CRM Automation with API & AI

@Microlent

Hello, I am Dr. Rajesh Rolen, PhD in Computer Science & Engineering, with experience of over 20+ years in API Development, REST API, PostgreSQL, SQL, Software Architecture, Python, Django, CRM As a preferred freelancer in the top 1%, I have done 400+ projects here on freelancer.com, I have 4.9 ratings out of 5 on average, which showcases my quality of work and timely delivery. Key Highlights: - Free Hosting Support on the Cloud or any desired platform. - Free 3 months of post-delivery support to ensure that our client doesn’t face any challenges after the launch of the project. - Free Dedicated tester on projects to ensure quality delivery, so clients don’t need to act as a tester. - 10+ Years experience UI/UX team to ensure intuitive UI. Portfolio: https://www.freelancer.com/u/Microlent Please open the chat and send me a message, so we can have a more detailed discussion about the project to give you the project timeline and cost. Thank you for considering my services. I look forward to engaging in a productive conversation and understanding how I can be of assistance in bringing your project to life. Regards Rajesh Rolen

@AwaisChaudhry

Hello, I can help build your focused Python AI CRM automation MVP with a maintainable architecture and clear milestone boundaries. I’ll structure the backend around controlled functions so the AI can analyze leads and recommend actions without unrestricted CRM access. My approach would be to create a modular Python service with a reliable CRM API client, configuration and authentication handling, PostgreSQL persistence, and well-defined API Development endpoints. The workflow can retrieve structured lead data, validate AI-generated decisions, update CRM records safely, and capture errors, audit logs, and outcomes for later review. I’ll also include schema design, defensive validation, retry-aware integration handling, pytest coverage for core paths and edge cases, and setup documentation so the project is straightforward to extend. The architecture can remain flexible for future workflows, additional LLM tools, synchronization, reporting, and production deployment. I’m strongest in Python backend architecture, database-driven systems, API integration, and practical SQL/data processing. I’m available to discuss the CRM’s authentication model, webhook or polling requirements, and the first workflow so the initial milestone stays focused and testable. Which CRM and AI provider will be used, and should the first workflow be triggered by webhooks, scheduled polling, or both? I’m interested in supporting the longer-term evolution after the MVP as well. Best regards, Muhammad

@ZohaibRoy

⭐⭐⭐⭐⭐ Build Your AI-Powered CRM Automation with Python Expertise ❇️ Hi My Friend, I hope you're doing well. I reviewed your project requirements and see you're looking for a skilled Python developer for your AI CRM automation. Look no further; Zohaib is here to help you! My team has successfully completed 50+ similar projects for CRM automation. I will create a robust backend system, integrate APIs, and implement AI workflows efficiently within your budget. ➡️ Why Me? I have 5 years of experience in Python development, focusing on backend systems and API integration. My skills include database design, automation workflows, and error handling. Additionally, I have a strong grip on FastAPI, Django, and SQL, which will ensure a smooth implementation of your project. ➡️ Let's have a quick chat to discuss your project in detail. I can provide samples of my previous work and demonstrate how I can add value to your CRM automation. Looking forward to our chat! ➡️ Skills & Experience: ✅ Python Development ✅ CRM API Integration ✅ REST API Development ✅ Database Design ✅ Data Retrieval ✅ AI/LLM API Integration ✅ Automation Workflows ✅ Error Handling ✅ Logging ✅ Automated Testing ✅ Technical Documentation ✅ Git Version Control Waiting for your response! Best Regards, Zohaib

@neerajdhameliya

Hello, Answers to your questions: 1. I build Python-based backend automations, REST API integrations, CRM workflows, structured data processing, and AI/LLM integrations, focusing on reliable and maintainable solutions. 2. I recently built a Lead Scoring system using n8n, Close CRM, Google Sheets, Slack, and financial APIs. It validates leads, processes business data, scores prospects, updates CRM records, and alerts the team about high-value leads. 3. I’d use a FastAPI/Python backend with a database, AI/LLM layer, validation logic, controlled CRM actions, and logging. The AI would return structured recommendations, while Python validates and executes approved CRM actions. 4. Strongest areas: Python, API/CRM integrations, automation workflows, structured data, and AI/LLM integration. 5. Availability: Monday-Friday, 9.30 AM-7:00 PM IST, 40 hours/week. I’m interested in starting with the MVP and continuing as the system expands. Best, Niral

@extreamcode

Hi there, I can see the hidden risk here: the workflow will only work if the CRM, Python backend, and AI layer stay tightly controlled and observable. That’s exactly the kind of architecture I build cleanly. I’ve worked on Python API integrations, database-driven business logic, and automation systems where structured data moves safely between services. For your MVP, I’d set up a practical FastAPI-style backend, CRM client, schema design, workflow endpoints, logging, and tests so the AI recommends actions without direct uncontrolled access. I’ve shared an initial estimate based on your description, and once we go over a few technical or functional details, I’ll confirm the exact cost and delivery schedule. If you’d like, I can start by mapping the CRM → Python → AI flow and locking the first milestone scope. Which CRM platform and AI provider are you planning to use for the first milestone? Which CRM platform and AI provider are you planning to use for the first milestone? Looking forward to your reply so we can finalize the exact plan. Thanks, Asad

@imraz2016

Hi, I can build the initial Python AI CRM automation MVP and structure it so additional workflows can be added cleanly later. I’d use FastAPI + PostgreSQL + controlled LLM functions, keeping the AI behind validated backend actions rather than giving it unrestricted CRM access. The milestone can include the CRM API client, authentication, schema, endpoints, one complete AI workflow, logging/error handling, pytest coverage, and setup documentation. My strongest areas for this project are Python, REST APIs, structured data processing, AI/API integration, and workflow automation. I’m available to start immediately and can commit consistent weekly hours.

@nikhilgarg96

Hello Greetings, After reviewing your project description, I feel confident and excited to work on this project for you. But I have some crucial questions to clarify. Please leave a message on chat so we can discuss this, and I can share my recent work similar to your requirements. Thanks for your time! I look forward to hearing from you soon. Best Regards.

@Rekhathakur

Hi, I have strong experience with Python backend development, REST APIs, database design, AI/LLM integrations, and automation workflows. I can help you build a clean and scalable MVP that can later expand into multiple CRM and AI workflows. My approach would be to create a structured architecture where the CRM API, Python backend, AI layer, and database remain separate. The AI would analyze structured lead data and return controlled recommendations, while backend functions validate and execute approved actions in the CRM. For the first milestone, I can deliver the Python project structure, CRM API client, authentication/configuration, database schema, API endpoints, one complete AI workflow, logging, error handling, automated tests, and setup documentation. I am strongest with Python, FastAPI, REST APIs, PostgreSQL, SQL, LLM APIs, Pandas, and pytest. I’m interested in a long-term collaboration and can build the MVP with clean, maintainable architecture for future automation and AI expansion. With regards, Rekha

@sufyanasmat38

Hello, I have strong experience with Python, FastAPI, PostgreSQL, REST APIs, CRM integrations, LLM APIs, automation, and structured data processing. I can build the CRM to Python to AI workflow with controlled backend functions, secure API authentication, validation, logging, error handling, and automated tests rather than giving the AI direct CRM access. I’ll deliver the first milestone with a clean project structure, CRM client, database schema, working AI workflow, API endpoints, tests, and setup documentation, with architecture ready for future automation and production scaling. I can start immediately and would be happy to discuss the CRM API and first workflow.

@toriquldev123

Hello dear, Greetings from Md. Toriqul Islam! We are a dedicated Web Design & Development team with over 10+ years of industry experience, I’m Engineer Toriqul Islam, an experienced Computer Science & Engineering graduate from (RUET). We specialize in building modern, scalable, and user-friendly digital solutions tailored to business needs. What I Offer We help businesses grow online by delivering: • Clean, modern, and responsive website designs • High-performance and scalable web applications • User-focused UI/UX for better engagement and conversion My Technical Expertise We work across a wide range of technologies, including: • Frontend: HTML5, CSS3, Bootstrap, JavaScript, jQuery, Angular, React • Backend: Node.js, PHP, Laravel, .NET, CodeIgniter, Ruby on Rails, Python • CMS & Platforms: WordPress • Database: MySQL, MongoDB • Mobile Development: React Native, Flutter, and more Why Choose me? ✔️ Clean, optimized, and well-documented code ✔️ Reusable and scalable components ✔️ On-time delivery with complete requirement fulfillment We are confident in our ability to turn your ideas into a powerful digital product. Let’s discuss your project and make it a success. Looking forward to working with you! Best Regards, Md. Toriqul Islam

@rajat07me

The key part here is not just wiring a CRM to an LLM, but keeping the AI inside controlled backend actions so it can recommend and classify without touching CRM records blindly. For an MVP like this, I’d structure it around a clean Python service layer, a dedicated CRM client, an AI decision layer with guarded function calls, and audit-friendly logging so every lead action is traceable. I’ve worked on Python backends that combined API integrations, structured data processing, database operations, and automation flows where reliability mattered more than flashy AI output. Strongest areas on this stack are Python, REST API design, SQL/database modeling, and integrating LLM APIs in a way that is testable and maintainable rather than loosely stitched together. A similar system I’ve handled involved pulling business records from an external platform, validating them through backend rules, enriching them with AI-assisted classification, and pushing status/task updates back through API endpoints. I’m available around 30-40 hrs/week. - Which CRM are you connecting first? - Do you already have the lead categories/next-action rules defined, or should those be designed in the MVP?

@denisSolution

Hi, I'm Denis, a full-stack developer specializing in Python backends that integrate external APIs with AI workflows and structured data processing. This is exactly the kind of work I do well. I've built systems where a backend acts as a controlled intermediary between external services and AI operations. The key insight is treating the backend as the decision-maker, not just a pass-through. The AI analyzes data, but the backend validates, applies business logic, and manages CRM state. This keeps things predictable and auditable. For your project, I'd start by mapping the CRM API and designing a clean database schema mirroring relevant data structures. Then I'd build a FastAPI service with endpoints handling retrieval, AI processing, and updates. The AI integration uses structured prompts with clear input/output contracts, token efficiency, and proper error handling for unexpected responses. I'm strongest with FastAPI, PostgreSQL, and designing testable, extensible APIs. I've built similar multi-step workflows and structure code so adding new workflows later doesn't require rearchitecting. The first milestone is realistic. I'll deliver a solid foundation with one working workflow, proper logging, and tests giving you confidence in the system's behavior. I'm available full-time and genuinely interested in continuing beyond the initial phase. I can start right away. Let's discuss the details. Thanks, Denis.

@Solutionzhere

SolutionzHere has built comparable Python/FastAPI backends, CRM integrations, structured data pipelines and controlled LLM workflows. We’ll architect this as CRM → FastAPI → validated function layer → AI/LLM → CRM, keeping AI permissions tightly scoped, with PostgreSQL, logging, retries and pytest coverage. MVP: 7–10 business days Fixed milestone: $1,250 USD Includes architecture, CRM client, database, one AI workflow, tests and documentation. We’re also available for the longer-term roadmap. Key question: Which CRM will the MVP integrate with, and do you already have API credentials/documentation?

@DeveloperStation

Hi, We built an internal automation system that encodes business-development logic into AI-driven workflows on a Flask and OpenAI backend, retrieving structured data, generating recommended actions, and running them through controlled functions rather than giving the model free rein. That last part matches your design closely: the AI should propose, the backend validates, the CRM updates. BD Automation: internal MangoCoders tool, evidence-backed AI workflows. One question on the first milestone. Is the CRM API third-party (HubSpot, Zoho, Pipedrive) or a custom in-house one? That decides whether the CRM client wraps a documented SDK or needs schema discovery first, which changes error handling and retry design. I'd start with FastAPI, PostgreSQL, and a thin AI service layer so each workflow stays testable with pytest. Strongest with Python backends and API integration. Which CRM are we connecting? Adil

@PINESCRIPTERR

Hi, I can build the first milestone as a secure FastAPI service with a dedicated CRM adapter, PostgreSQL persistence, and a controlled AI workflow. My relevant work includes an AI Agent API using Python, FastAPI, PostgreSQL, Redis, Celery, structured LLM outputs, tool restrictions, persistent workflow state, human approvals, and automated tests. For this MVP, the flow would be: CRM event → normalized lead record → schema-constrained AI analysis → deterministic validation → approved CRM action → complete audit log. This keeps the model from accessing the CRM directly. My strongest areas are Python, FastAPI, API integrations, PostgreSQL, asynchronous workflows, LLM tooling, testing, and documentation. I’m also available for ongoing development after the initial milestone. Three technical questions: 1. Which CRM and authentication method will be integrated first? 2. What lead categories and recommended actions should the AI produce? 3. Which actions require human approval before updating the CRM? Best regards, Houssame

@ImranAli01

Hi there, I went through your project description and understand you need a Python-based CRM automation MVP connecting a CRM API, structured backend, database, and controlled AI workflow. I will build the backend using Python and FastAPI, with a clean CRM API client, secure configuration, PostgreSQL/MySQL, REST endpoints, and structured data processing through Pandas where appropriate. I will implement the CRM → Python → AI flow so the LLM only analyzes data and proposes actions through controlled backend functions, while deterministic validation controls what can be written back to the CRM. I will add robust error handling, structured logging, edge-case handling, pytest coverage, Git-based development, and clear setup documentation. The first milestone will include the project structure, authentication, schema, API endpoints, one complete AI workflow, testing, and documentation, with architecture kept extensible for future agents and automations. Could you confirm which CRM/API will be used for the first milestone and whether PostgreSQL is your preferred database? I will share a project blueprint within 24–48 hours of award and begin immediately. Kind Regards, Imran Ali

@mayankinnovative

With over two decades of experience in PHP-based development and a specialization in WooCommerce, Laravel, and WordPress, I bring valuable skills to your Python AI CRM Automation project. My focus on clean, scalable solutions aligns well with your long-term vision for this project. I understand that you’re looking for more than just a one-off task but rather someone you can rely on through multiple stages of the project. Clients often choose to continue working with me because they appreciate my ability to understand complex requirements swiftly and deliver robust, reliable results. As requested, let me illustrate my skillset with an example and how it relates to your project. Recently, I built a custom order-flow system for an e-commerce client using WooCommerce, Laravel backend development, and various API integrations. This system streamlined their order processing, improving efficiency drastically while eliminating common bottlenecks they faced before. I see similarities between this project and yours as you need automation to manage leads and customer tasks - this calls for an architecturally-sound solution which I have excelled in providing.

@sedawy

As a seasoned DevOps and Cloud Engineer with 15+ years of experience, I bring a wealth of knowledge to the table that not many can match. I have a strong command over Python, which is your preferred language, making me well-equipped to handle your project. Having deployed ERP systems and implemented CI/CD pipelines for clients across various verticals internationally, I understand the demands of scaling and securing an application. I am particularly skilled in building robust API integrations, structured data processing and I am at ease when working with databases like PostgreSQL. These skills will prove vital in architecting a CRM → Python → AI workflow that will extract the lead information, analyze it through AI layer efficiently, suggest next actions to be performed proved by API calls to the CRM nerately update appropriate CRM records/tasks while keeping logs after validating these actions for future references. Apart from delivering an excellent first milestone including well-structured Python code, restful APIs, secure ORM design and basic automated tests; I am also looking forward to a long-term partnership with you as your project embarks on exciting possibilities for CRM workflow automation. Let my skills and wealth of experience speak for themselves as you make your decision moving forward. My full-time availability ensures that your potential needs are always prioritized-growing together!

@ssquare489

The controlled CRM → Python → AI pattern is the right architecture here, especially your requirement that the AI recommends actions through backend functions rather than directly manipulating CRM records. I’d keep the first milestone deliberately modular so additional workflows and agents can be added without rebuilding the integration layer. Relevant experience: I work across backend APIs, CRM integrations, webhooks, structured data processing, automation, databases, and LLM-powered workflows. For this MVP I’d use FastAPI, PostgreSQL, Pydantic models, pytest, and a clean service/repository structure. Relevant example: Kingmovers, where I built integrations around SmartMoving CRM, RingCentral, CallRail, WebSockets, webhooks, lead routing, analytics, and automated CRM workflows. Architecture: CRM webhook/polling → API client → validation/normalization → database → AI service → controlled action validator → CRM update/task creation → audit log. The LLM would never receive unrestricted CRM credentials or write access. Strongest areas: API/backend architecture, CRM integrations, workflow automation, SQL/data modelling, webhooks, and AI API integration. Availability: 20-25 hours per week, with room to continue into later milestones if the MVP goes well. I’d also include idempotency, retry handling, structured logging, test fixtures, and environment-based configuration from the first milestone so production hardening later is straightforward.