AUTOMATION
78%
Tasks Auto-Generated
Applied AI, RAG Systems, & Backend Engineering
AUTOMATION
Tasks Auto-Generated
ACCURACY
Context Retrieval Score
LATENCY
Avg Agent Response
THROUGHPUT
Faster Than Manual PM
UPTIME
Backend Reliability
When project complexity outpaces manual coordination
Traditional task management fails when tools cannot reason. Relying on manual updates creates a synchronization gap that leaves teams reactive rather than strategic as project goals evolve.
The Intellema Design Challenge
Modern task platforms rely on manual configuration and lack the contextual intelligence to reason over evolving project goals. This project required a multi-agent system capable of autonomously managing tasks by synthesizing project documentation and complex dependencies.
The architecture combined high-accuracy RAG pipelines with Knowledge Graphs and a production-grade FastAPI backend. This hybrid approach allowed for human-like reasoning and adaptive automation, ensuring that task prioritization remains aligned with real-time project data.
Scalable backend built with FastAPI, AWS, and PostgreSQL, enabling seamless multi-server communication via MCP.
Hybrid system combining knowledge graph reasoning with dense vector retrieval for precise understanding of context and task dependencies.
Collaborative framework of specialized AI agents that parse goals, generate structured subtasks, and optimize workloads dynamically.
Airflow-based scheduling layer to manage RAG execution cycles with high reliability, scalability, and low latency.
