Built with OutSystems, J.A.R.V.I.S. is an AI assistant designed to move beyond simple chat, by orchestrating specialized AI agents to handle real-world business tasks and boost the productivity of developers and tech leads.

Why J.A.R.V.I.S. and Orchestration?

The future of productivity lies in a network of specialized agents, not a single, all-knowing model. J.A.R.V.I.S. embraces this approach:

• Modularity and Scalability: It is a collection of specialized AI agents coordinated by a decision-making layer. This design allows you to easily swap, upgrade, or extend agents without rewriting the whole system.

• Intelligent Orchestration: OutSystems handles the orchestration, integrations, and UI. The Decision Maker acts as air traffic control, evaluating intent and selecting the right agent(s) for the job.

• Focused Agents: Each agent has one job (e.g., Calendar Agent, Email Agent, Project Manager Agent) , which avoids creating a bloated "do-everything" model that fails at the details.

RAG: Reliable, Data-Grounded Answers

To prevent Large Language Models (LLMs) from "hallucinating" (making things up) , J.A.R.V.I.S. uses Retrieval-Augmented Generation (RAG).

• This pipeline ensures that responses are grounded in your company’s data.

• It converts the user query into an embedding, runs a similarity search to pull relevant knowledge, and feeds it to the LLM for the final answer.

• This means developers can plug in their own data—like project documentation—and trust the assistant to stay fact-based.

The Value for Your Enterprise

J.A.R.V.I.S. demonstrates how OutSystems and AI orchestration combine to deliver real productivity gains.

• Focus on High-Value Tasks: Agents offload repetitive work like juggling calendars, summarizing emails, or manually updating project data.

• Practical Model: It is a practical model for how teams can build assistants that extend their workflows, save hours of repetitive work, and ground outputs in reliable data.

• Lesson Learned: Start small, build reusable pieces, and keep humans in the loop for validation.

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