The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
Back to feedPost
ResearchX – Autonomous Deep Research AI Agent
ResearchX is a production-ready autonomous research agent that performs end-to-end research with minimal human input.
Instead of simply answering questions, the agent plans research tasks, searches multiple trusted sources, evaluates information quality, retrieves supporting evidence, and generates structured reports with citations.
Built using a multi-agent architecture, the system combines planning, retrieval, tool calling, memory, and iterative reasoning to handle complex research tasks while reducing hallucinations through grounded retrieval and verification.
Features:
Autonomous Planning
Multi-Agent Workflow
Web Search Integration
PDF Analysis
RAG Pipeline
Citation Generation
Long-Term Memory
Report Generation
Source Verification
Evaluation Framework
Tech Stack:
Python • LangGraph • FastAPI • Tavily • ChromaDB • PostgreSQL • Redis • Docker • OpenAI • Claude
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
Challenges
View all
Related posts
Check This...
Another productive day — this time showcasing my Hand Gesture Mouse Control project. A Python-based computer vision project that lets you control your computer mouse using hand gestures in real time.
👆 Index finger → Move the cursor
👌 Pinch index + middle finger → Click
Built...
AI Lead Qualification & Appointment Automation System
AI Lead Conversion Platform — Telegram, CRM & Automated Scheduling
Designed and developed an AI-powered lead conversion system that handles incoming Telegram conversations from first contact to qualification, CRM synchronization, and appointment booking.
The AI works with conversation history, lead profile data, unanswered questions, current funnel stage, available actions, and verified CRM data to determine the next appropriate step and generate structured responses.
The system automatically creates and updates leads in the CRM, manages qualification stages, books meetings, generates Yandex Telemost links, sends reminders, handles rescheduling, and escalates exceptional cases to a human manager.
The architecture includes dialogue state management, message deduplication and batching, PostgreSQL persistence, concurrency protection, validation before actions are executed, and safeguards against sending unverified or prohibited information.
This is not just an AI chatbot — it is an automated sales workflow that connects Telegram, AI, CRM, scheduling, and human escalation into one controlled process.
AI makes decisions within controlled business rules instead of operating as an unrestricted chatbot.
The concurrency safeguards and validation-before-actions detail is a strong distinction here—booking systems usually fail at the edges, not in the happy path. I’d expose a compact lead state to the operator (stage, next action, last unanswered question) so a human can resume...
AI agent products can easily feel too technical, too dense, or too abstract.
Agentix explores a calmer way to explain automation: a SaaS landing page built around clear product messaging, progressive storytelling, no-code workflows, agent monitoring, cost visibility, error tracking, and measurable business impact.
The visual direction avoids the usual heavy AI SaaS look, using landscapes, open space, modular interface elements, and focused conversion moments to make the product feel more trustworthy and easier to understand.
