Advanced AI Agent Platform Development

@installerpoint

Hello, I’m interested in building the AgentTide AI Agent Platform and understand that this is intended to be a reusable SaaS-style platform rather than a collection of disconnected chatbots. The key requirements I see are multiple specialized AI agents, shared configuration, usage metering, integrations, human approval controls, and a simple non-technical interface. The dashboard can then present usage transparently and provide the foundation for future subscription or usage-based billing. I can provide a modular, maintainable implementation rather than a collection of prompt-based demos, with the architecture designed around the longer-term AgentTide product. Best regards ADEEL

@raheel2k29

Hello, I’m interested in building AgentTide, and I understand that this is more than a basic AI chatbot. The platform needs a proper multi-agent architecture where each agent has a defined purpose, controlled actions, usage tracking and human approval before operational actions are executed. I would use the initial specification to finalize the exact milestone scope, particularly around third-party integrations, telephony, CRM providers, IoT protocols and AI/API costs. Third-party API, cloud, telephony and AI-model charges would be separate from the development fee. I can provide the complete source code and structure the system so additional agents and integrations can be added without rebuilding the entire platform. Regards Raheel

@onkarkulkarni8

Hi, I can help you with "Advanced AI Agent Platform Development" as per your given project description. We can discuss more in detail during a chat conversation when you are available. I've worked on many PHP projects in recent times. So I am confident on achieving your expected Goals. Please initiate a communication thread to discuss further and start with the project. ⭐ 5.0/5 from a recent client: "Good work delievered thank you for your patience" Final timeline and cost will be confirmed in chat after a complete understanding and documentation of the project expectations in detail.

@Zaiyan

The requirement for a suite of AI agents that can handle various tasks like lead qualification and document Q&A is crucial for streamlining operations. I’d approach this by developing each agent with a focus on user-friendly configuration, allowing your team to manage workflows without technical expertise. The plan involves first building the core functionalities for the AI Receptionist and Lead Response Agent, ensuring they can integrate smoothly with your existing CRM. Next, I’d set up the Document Q&A Agent, allowing for easy uploads of policies and FAQs. Before starting, I’d confirm the specific CRM you’re using to ensure compatibility. With a 98% completion rate on 126 projects since 2013, I have the experience needed for this scope. How do you envision the user interface for configuring these agents?

@mayankinnovative

I fully understand the structure of AgentTide’s multi-agent architecture (Receptionist, Lead Response, Document Q&A, Reporting, Workflow, and IoT Monitoring) and its usage-based metering platform. Approach: The platform will be built using modular microservices (FastAPI/Node.js + LLM Orchestration). It will feature a RAG pipeline (with citation support) for Document Q&A, a low-latency stack (Twilio/WebRTC) for voice/chat, and event-driven workflows for CRM synchronization. An analytics engine for spreadsheet parsing and auto-charting, along with an MQTT/WebSockets alert system for IoT telemetry, will be integrated. The user-friendly configuration console will incorporate a "human-in-the-loop" approval system, role-based permissions, and precise usage-based billing via Stripe. 1. Which models or providers (e.g., OpenAI, Anthropic, or self-hosted open-source models) do you prefer for the LLM backend? 2. Should all six agents be launched simultaneously in the first phase, or should we start with a core MVP set (e.g., Receptionist + Lead Response)? 3. Through which protocol (MQTT, Webhooks, or Kafka) will the device telemetry data be ingested for the IoT monitoring agent? I will successfully deliver this platform to the required standards, ensuring high reliability, data security, and a scalable architecture.

@modesorehari6

⭐⭐⭐Hi there, From Your Vision To Successful — I will take responsibility⭐⭐⭐ I can build a reliable AI Agent Platform with AI reception, lead qualification, document Q&A, reporting, workflow automation and IoT monitoring. I have relevant experience in AI agents, AI chatbot development, PHP and AI workflow automation with a strong focus on CRM integration and practical business automation. My plan is to develop each agent with clear approval controls and usage metering while creating a simple setup interface for non technical users. I will integrate chat and call handling, lead scoring, CRM syncing, document based cited answers, spreadsheet analysis, appointment workflows and real time IoT alerts with secure scalable architecture. I am free to start immediately and can dedicate my time to this project. I respect your suggestions and requirements throughout development and will communicate clearly at every stage. I am also interested in building a long term working relationship and supporting future improvements. Thanks

@jaroslavcaprata

Hi, I can help build AgentTide as a scalable AI agent platform combining LLMs, automation, integrations, and a simple SaaS experience. I can work across the complete platform, including: • AI receptionist for chat/voice and appointment booking • Lead response, qualification and CRM synchronization • RAG-based document Q&A with cited sources • Spreadsheet analysis and automated reporting • Workflow agents for bookings, reminders and follow-ups • IoT monitoring and intelligent alerts • Human approval before external actions • Usage metering and agent-level billing • Configurable agent setup for non-technical users I’d design the agents as modular services with clear tool permissions, structured workflows, logging and human-in-the-loop controls so actions such as bookings, messages and alerts remain auditable and controlled. I can also build the supporting APIs, authentication, database, integrations and SaaS infrastructure around the agents rather than treating them as isolated AI features. I’d be happy to start with the core agent architecture and then build the individual agents as reusable components. Best regards, Jaroslav

@albert1025dev

==== Hi - Albert here ==== **“MODULAR AI AGENT PLATFORM WITH APPROVAL-BASED AUTOMATION AND USAGE BILLING”** — Build AgentTide into a centralized platform that automates enquiries, lead qualification, document Q&A, reporting, scheduling, and IoT monitoring. I’d approach this with a modular architecture, a PHP-compatible backend where appropriate, secure API integrations, and a simple configuration dashboard. Each agent would have defined permissions, usage tracking, transparent billing, audit logs, and approval gates before bookings, messages, or alerts are executed. I’d start with an MVP covering the highest-priority agents, then expand through tested modules with clear documentation. Which agents are essential for the first release, and do you already have preferred AI models, telephony services, and CRM integrations? Looking forward to work with you

@UzeeTech

AgentTide is a strong brief — six specialised agents under one roof, metered and gated behind client sign-off. The smart move is shipping the platform spine first, so every agent after the first two becomes cheap to add. Phase one: a shared foundation in Python/FastAPI — agent registry, LLM tool-calling layer, usage metering, and a sign-off queue so nothing fires without approval. Then: Lead Response (instant replies, qualifying questions, lead scoring, CRM sync) and AI Receptionist (24/7 call/chat, appointment booking, human handoff). A simple setup screen lets the client configure agents without technical knowledge. I'm currently building an AI-powered website-generation platform, so multi-step LLM pipelines with tool use and guardrails are my day-to-day work. Two questions: which CRM should the Lead Response Agent sync into, and which telephony provider should the receptionist use? If this phasing sounds right, I'll break phase one into milestones and we can lock the final scope together.

@prachia77

Hi, AgentTide is a strong fit for my AI development experience, particularly the combination of AI agents, RAG, document intelligence, workflow automation, and API-based integrations. I can help build modular agents for lead qualification, document Q&A with cited sources, reporting, appointment workflows, and operational monitoring. I’d structure the platform so agents share common services for authentication, knowledge retrieval, integrations, usage tracking, approvals, and auditability rather than creating isolated systems. I have hands-on experience with Python, FastAPI, RAG pipelines, Gemini embeddings, vector databases, MongoDB, Docker, and AI-agent workflows. I focus on grounded responses, reusable architecture, and human approval before actions such as booking, messaging, or notifications. I’d be happy to discuss the first agent you want to take into production. Best Regards, Webix Infotech India Pvt. Ltd.

@AhmedHashimPro

Hi, I'm a software architect with 11 years of experience, and the IoT Monitoring Agent is the part I know best. At DroneLeaf I own the AWS backend of a drone-fleet platform: MQTT over AWS IoT Core, 30+ Lambdas, DynamoDB, Cognito, and a role-based authorization platform shared by 8 Lambdas. On the AI side I built My Stream, a publishing platform with 7 LLM providers and Stripe billing, plus rag-knowledge-agent and llm-contract-router on my GitHub. How I'd structure it: 1. One shared core: tenants, users, roles, per-agent usage metering and Stripe usage billing. 2. Each agent as a module with its own setup screen, plus an approval queue so no booking, message or alert goes out without sign-off. 3. Document Q&A with RAG and cited answers. IoT agent subscribes to device telemetry over MQTT and explains issues in plain English. 4. Launch 1-2 agents as an MVP first, then add the rest. Two honest notes: the post lists PHP, but I'd build this in Node.js/TypeScript or Python. Voice call handling for the receptionist is new to me, so I'd scope it separately. Questions: 1. Which agent matters most at launch? 2. Which CRM should leads sync to? 3. Do you already have devices or data for the IoT agent? Best, Ahmed

@hojaifa1207

Hi, AgentTide needs a modular SaaS foundation where each agent shares authentication, billing, approvals, integrations, monitoring, and usage metering without becoming tightly coupled. I can build the platform around configurable AI workflows, RAG/document Q&A, CRM and scheduling integrations, reporting, human approval gates, IoT event handling, multi-tenant permissions, and transparent usage tracking with a simple non-technical setup experience. Let's discuss in chat to proceed further.

@gismodelta79

Hi! The idea of agents that do the busywork but never act without the owner's sign-off is a smart design, and it's close to what I already run in production: a multi-business platform of WhatsApp and web assistants that quote, check inventory and take orders by calling business APIs (tool/function calling), using Claude API and Google Gemini. Six agents plus metering and a setup screen is well beyond a 12,500-37,500 INR budget, so I'd suggest a first phase that fits: - Lead Response Agent: instant replies to new enquiries, qualifying questions, scoring, and sync to your CRM via its API. - Approval step: every outgoing message or booking waits for your sign-off before it is sent. - Document Q&A Agent: upload FAQs or price lists and get answers that cite the source passage. - Laravel/PHP backend with a simple setup screen and per-agent usage metering. - Workflow Agent (booking, confirmations, reminders) and the Report Agent as later phases. I have 10+ years with PHP/Laravel, MySQL, queues and scheduled jobs, plus n8n automation. Voice calls for the Receptionist would be a separate phase. Which CRM do you use, and which agent should come first?

@artechvisionn

Hey! I can handle this easily. I recently developed AI chatbot workflows and integrated AI agents into platforms 12 times, automating lead generation and sales tasks smoothly. For your AgentTide AI Agent Platform, I’d focus on building intelligent agents that manage telemarketing, sales follow-ups, and lead handling efficiently, reducing your team’s busywork. Here’s how I’d approach it: 1. Understand your current workflows and data sources for telemarketing and sales. 2. Develop AI agents that automate repetitive tasks, using PHP and AI APIs for smart responses and lead qualification. 3. Test the workflows end-to-end to ensure agents handle conversations and tasks reliably. 4. Provide clear documentation and support for future updates. I just finished a similar AI app integration that improved workflow automation and lead handling, so I’m confident I can deliver exactly what you need. Can you share more about the existing platform and the AI tools or APIs you want to use? Aakash P.S. Happy to discuss how AI agents can boost your team’s productivity anytime!

@kelleyg2002

Good Day! You're building a ⭕AI Agents + ⭕Workflow Automation agent platform. I've built similar project and have the architecture. I CAN DO THIS & I AM READY! I understand you need multiple AI agents that can handle enquiries, leads, documents, reports, bookings, and IoT alerts while keeping every action under user approval. I can help with building the agents, AI workflows, usage metering, CRM integration, and simple setup dashboard. Which agent would you like to build first? I have experience building AI powered applications and automation workflows with clean, scalable architecture. I can build this step by step and keep it easy to manage. Let's start discussing through the chat and get started! Regards, Kelley.

@MrShortFlow

No TOOL line needed. The core challenge here is not writing six agents from scratch but wiring one metered, auditable core — intake, scoring, CRM sync, document citation, scheduling — so every agent shares the same sign-off gate before anything is sent or booked. Delivery in steps: v1 within 3 working days covering the setup screen skeleton plus one working agent (Lead Response, since it has the clearest measurable output — scored, synced leads). Remaining agents (Receptionist, Document Q&A, Report, Workflow, IoT) added and wired to the same approval gate and usage meter over the following 2 days, ending in a full handover note. Two first decisions: build the approval gate as a single reusable confirmation step every agent must pass through, since transparency and sign-off are core requirements, not per-agent features; and start with Lead Response and Document Q&A agents first, since their scoring and citation logic is reusable across the other four. I do not promise native phone-call handling without your telephony provider's access, or IoT alerts without your device/API specs. Which CRM and data sources (leads, documents, device feeds) should v1 connect to first. Price: 17400 INR fixed · Timeline: 5 working days from access/brief Konrad

@akg84

Hi, I can help build your AgentTide AI Agent Platform as a modular AI automation system. I have hands-on experience with AI voice agents, AI assistants, appointment booking, CRM automation, lead qualification, Google Calendar and n8n workflows. For your platform, I can develop the core MVP including: • AI Receptionist for enquiries and appointment booking • Lead Response Agent for qualification and CRM sync • Document Q&A Agent for FAQs, policies and business documents • Report Agent for spreadsheet analysis and summaries • Workflow Agent for bookings, confirmations, reminders and follow-ups • Admin/configuration interface • Usage tracking and human approval controls I will structure the system modularly so additional integrations such as IoT monitoring can be added without rebuilding the platform. I can start immediately and work with clear milestones and regular progress updates. Regards, Makshud

@pandaymano8

As an AI and automation enthusiast with a strong background in PHP development, my skillset aligns perfectly with your project. I have had the opportunity to work on developing advanced AI chatbots and leveraging automation to streamline processes for businesses. What separates me is not only my technical competency, but also my commitment to understanding and delivering on client needs. I believe that's crucial for creating a product as intricate and impactful as the AgentTide AI Agent Platform. I possess extensive experience in building scalable digital solutions using platforms like WordPress, Python, React.js alongside APIs and databases management such as MySQL. These skills will aid in implementing and integrating your vision efficiently without compromising data security. Moreover, my domain knowledge extends to AI agent development and automation tools like n8n that are pivotal for your project's success. At heart, I'm a problem solver who uses technology intelligently to optimize productivity. With the AgentTide platform, I can help your team focus on strategic tasks, while ensuring your operations run smoothly round the clock. Let's collaborate to build an intelligent engine for your business that enhances efficiency, trims costs, and generates long-term value "

@digitaldotsent

I understand AgentTide as a multi agent platform where each agent, receptionist, lead response, document Q&A, report, workflow, and IoT monitoring, needs to run independently but share a common metered billing layer and a no code setup screen, with a human approval gate before any action goes out. That is a real architecture challenge, not just a single bot. My approach would be to build the core agents as n8n workflows for orchestration, backed by Postgres for usage metering, lead scoring, and conversation state, with Python services for the report generation and chart building where n8n hits its limits. For document Q&A I would use a RAG setup with embeddings and citation tracking. The approval gate would be a simple queue state in Postgres that holds any booking, message, or alert until the client confirms, exposed through a lightweight setup dashboard. All of this would run on a Hetzner server behind Caddy, with cron handling scheduled IoT checks and reminders. Given the fixed budget, which one or two agents do you want built and working end to end first, before scaling to the full suite. Syed, Digital Dots