AI Assistant SAAS Platform Development inspired by LindyAI
Budget: ₹75,000 – ₹150,000 INR
Project Overview
We're building a SAAS AI assistant platform similar to Lindy.ai. The platform will enable users to create custom AI agents that connect to their business apps (Gmail, Slack, CRM, etc.) to automate workflows and tasks through natural language commands. For the API, we can use embedded IPAAS vendors or open sourced. Building AI employees. I am seeking for a developer who is street smart in getting this product up in a short period. I will be paying the developer. If the developer's price is reasonable, we can talk equity and joining in as a cofounder.
Core Technical Requirements
1. AI Agent Logic & Reasoning Engine
Build a sophisticated AI agent capable of multi-step reasoning and task execution
Implement LLM orchestration using frameworks like LangChain or LlamaIndex
Create planning capabilities where the AI can break down complex requests into actionable steps
Develop context management and conversational memory
Integrate with LLM APIs (OpenAI GPT-4, Claude, or open-source alternatives)
2. iPaaS Integration Layer
Implement integration with Zapier, Make (Integromat), or n8n for app connectivity
Create a system for OAuth authentication flow management
Build abstraction layer for triggering actions across 100+ business applications
Handle webhook management for real-time updates from connected apps
3. Data Architecture & Storage (Supabase Focused)
Design and implement database schema using Supabase (PostgreSQL)
Implement PGVector for RAG (Retrieval-Augmented Generation) and document memory
Build secure credential management with encryption for user app tokens
Create real-time chat system using Supabase's real-time capabilities
Design efficient storage strategy for chat logs, user data, and document embeddings
4. User Interface & Experience
Develop a responsive, modern frontend using React/Next.js or Vue/Nuxt
Build a real-time chat interface with streaming responses
Create a no-code agent builder workspace for workflow customization
Implement clean, intuitive UI for connecting apps and managing agents
5. Backend Infrastructure
Build robust backend API using Node.js/Express or Python/FastAPI
Implement background job processing for long-running tasks
Create comprehensive logging and audit trails for AI actions
Build user authentication and multi-tenant data isolation
Develop error handling and retry mechanisms for external API calls
Required Skills & Technologies
Must-Have:
Full-stack development experience
AI/ML Integration: Proven experience with LangChain, LlamaIndex, or similar agent frameworks
Supabase Expertise: Deep knowledge of PostgreSQL, real-time features, and PGVector
iPaaS Integration: Hands-on experience with Zapier, Make, n8n, or similar platforms
Modern Frontend: React, Vue, or similar framework with state management
Backend Development: Node.js/Python with API design experience
Authentication: OAuth 2.0 flows and secure credential management
Nice-to-Have:
Experience with workflow orchestration (Airflow, Temporal)
Knowledge of vector databases and RAG implementations
Previous experience building AI agent products
DevOps skills (Docker, deployment, monitoring)
Experience with real-time applications (WebSockets, SSE)
If you feel there's a better and cheaper way , lets talk
We're building a SAAS AI assistant platform similar to Lindy.ai. The platform will enable users to create custom AI agents that connect to their business apps (Gmail, Slack, CRM, etc.) to automate workflows and tasks through natural language commands. For the API, we can use embedded IPAAS vendors or open sourced. Building AI employees. I am seeking for a developer who is street smart in getting this product up in a short period. I will be paying the developer. If the developer's price is reasonable, we can talk equity and joining in as a cofounder.
Core Technical Requirements
1. AI Agent Logic & Reasoning Engine
Build a sophisticated AI agent capable of multi-step reasoning and task execution
Implement LLM orchestration using frameworks like LangChain or LlamaIndex
Create planning capabilities where the AI can break down complex requests into actionable steps
Develop context management and conversational memory
Integrate with LLM APIs (OpenAI GPT-4, Claude, or open-source alternatives)
2. iPaaS Integration Layer
Implement integration with Zapier, Make (Integromat), or n8n for app connectivity
Create a system for OAuth authentication flow management
Build abstraction layer for triggering actions across 100+ business applications
Handle webhook management for real-time updates from connected apps
3. Data Architecture & Storage (Supabase Focused)
Design and implement database schema using Supabase (PostgreSQL)
Implement PGVector for RAG (Retrieval-Augmented Generation) and document memory
Build secure credential management with encryption for user app tokens
Create real-time chat system using Supabase's real-time capabilities
Design efficient storage strategy for chat logs, user data, and document embeddings
4. User Interface & Experience
Develop a responsive, modern frontend using React/Next.js or Vue/Nuxt
Build a real-time chat interface with streaming responses
Create a no-code agent builder workspace for workflow customization
Implement clean, intuitive UI for connecting apps and managing agents
5. Backend Infrastructure
Build robust backend API using Node.js/Express or Python/FastAPI
Implement background job processing for long-running tasks
Create comprehensive logging and audit trails for AI actions
Build user authentication and multi-tenant data isolation
Develop error handling and retry mechanisms for external API calls
Required Skills & Technologies
Must-Have:
Full-stack development experience
AI/ML Integration: Proven experience with LangChain, LlamaIndex, or similar agent frameworks
Supabase Expertise: Deep knowledge of PostgreSQL, real-time features, and PGVector
iPaaS Integration: Hands-on experience with Zapier, Make, n8n, or similar platforms
Modern Frontend: React, Vue, or similar framework with state management
Backend Development: Node.js/Python with API design experience
Authentication: OAuth 2.0 flows and secure credential management
Nice-to-Have:
Experience with workflow orchestration (Airflow, Temporal)
Knowledge of vector databases and RAG implementations
Previous experience building AI agent products
DevOps skills (Docker, deployment, monitoring)
Experience with real-time applications (WebSockets, SSE)
If you feel there's a better and cheaper way , lets talk