AgentBridge (codename "AGENT") — promises to replace humans in offices

Add agentic power to your work! Automate tasks and your work without sacrificing your privacy.
We're happy to put this powerful tool in your hands to automate your business while reducing staff costs, providing you with the most advanced AI technology in the office automation industry.

AgentBridge is a self-hosted server that runs AI agents with two interfaces in a single process: a full-screen chat terminal (TUI) and a standard HTTP API compatible with OpenAI.

Chat in the terminal while scripts, bots, and apps use the same agents on the same port:
same process, same conversations, no bridges, no synchronization.

Why teams choose this architecture
AgentBridge is built on the AIOrchestrator library model: one runtime, one agent core, and one consistent operational flow across terminal and API. The result is faster execution, lower integration overhead, and stronger control than traditional multi-server MCP setups. Read the white paper: Why the AIOrchestrator Library Model Outperforms Traditional MCP Deployments.

Install & download

The Download for your OS button detects your platform and starts the right archive
(~460 MB, self-contained — no .NET installation needed, Kokoro TTS voices included).
Prefer the terminal? One line is enough:

The one-liners download the latest release for your platform into ~/.agentbridge
(%LOCALAPPDATA%\AgentBridge on Windows) and print how to start it. Direct links:

Built on the AIOffice agent orchestrator
(AIOrchestrator), AgentBridge brings the agents to everything:

• You, in the terminal — a modern chat UI (Terminal.Gui) with streaming replies, a /
  command palette, file attachments, voice dictation and in-process neural text-to-speech.
• Any OpenAI-compatible client — SDKs, bots and scripts talk plain
  POST /v1/chat/completions to the same agents. No plugin, no custom SDK, no lock-in.

Demo gallery

A visual showcase — new demos are added here as they are produced.

Terminal UI — streaming agent replies, the / command palette with live filtering, and
the status bar that follows the server, model, session and context window:

PowerPoint-style presentations generated by the agent — describe the deck you need and
the agent designs the slides for you:

Detailed PDF market & financial analysis reports generated by the agent — request a market analysis, financial analysis, or report of any kind and the agent will use proprietary "AI Exoskeleton" augmented artificial intelligence algorithms to generate accurate PDF documents with authoritative sources such as Deloitte, KPMG, E&Y, etc.:

Real office documents generated from a plain prompt — ask for an invoice or an employment contract, attach the data, and the agent produces the finished document from the official templates, ready to use in the office. These two were generated end-to-end by the agent (material check → DOCX) in a real use case:

This is an employment contract in Word format, completely generated by the agent with a simple request. The AI agent has no limitations; it can create any type of document, remember the style and maintain it for future use, or modify it if necessary to customize it or add new elements.

An Excel spreadsheet (data table + chart, single A4 page) created by the agent on request from a plain prompt — the user asks for a workbook in English, the agent builds it with the SpreadsheetTool (data, styles, chart, A4 page setup) and delivers the finished file:

Agent Bridge: Your AI Assistant for Office Work

Agent Bridge is a tool that allows you to connect to your preferred AI, transforming it into your personal assistant: a tireless worker capable of handling office tasks such as drafting complex documents, working with spreadsheets, interacting with email, and performing internet-based activities—all while having full awareness of your company's knowledge base: clients, documents, products, and everything stored in your archive.

Agent Bridge positions itself as a cloud platform for businesses or private individuals seeking AI solutions. Everything uploaded to the cloud area becomes part of the AI's knowledge, enabling it, with full understanding of your documents and data, to work as a tireless employee and carry out office work. The product fits within the enterprise segment, capable of storing and managing even several terabytes of data, and can generate PDF documents with a level of detail and precision that is unmatched.

Our Agentic AI is designed to be installed on standalone devices, such as mini PCs and dedicated AI hardware, effectively transforming them into truly autonomous agents. An agentic system, in fact, is not simply meant to execute a task on command but is built to pursue a complex objective with full autonomy, and its key characteristics go well beyond running a single instruction. First and foremost, it possesses planning and reasoning capabilities: when faced with a request like "organize a trip to Tokyo," the system does not merely react but breaks the goal down into a series of logical sub-goals, such as booking a flight, selecting a hotel, and creating a coherent itinerary. This planning phase is then put into action through the active use of external tools: the agent is capable of calling APIs, executing code, searching the internet, and interacting with databases or other applications to independently gather information and take action. To manage this level of complexity, the system maintains a structured memory, both short-term and long-term, of the actions taken and the information collected, allowing it to adapt its plan along the way. Its operation is based on a continuous loop of execution and feedback: it performs an action, observes the result – for instance, an error during a flight search – evaluates whether this result is bringing it closer to the final goal, and accordingly adjusts its next step. This cycle of action, observation, and adaptation continues until the objective is fully achieved. Our hardware support strategy targets a range of devices, starting with high-performance processors like the 16-core AMD Ryzen AI Max+ 395, the 12-core AMD Ryzen AI 9 HX 370, the NVIDIA GB10 Grace Blackwell Superchip, the 14-core Arm-based NVIDIA Jetson T5000, and the 20-core NVIDIA RTX Spark. For the entry-level segment, we maintain compatibility with ARM-based technology, specifically supporting the Rockchip RK3588, Rockchip RK3576, Qualcomm Snapdragon 865, Qualcomm Snapdragon X2 Elite, MediaTek Genio 420, and MediaTek Genio 360 chipsets.

Innovative Features

• AI Assistant Available 24/7 via SIP Protocol
  The system provides a fully integrated AI agent that can be reached at any time through SIP‑based telephone access. It operates as a dedicated personal assistant capable of natural voice interaction, immediate task execution, and uninterrupted availability. Unlike a human secretary who may be distracted or unavailable, this assistant remains consistently focused, reliable, and committed to carrying out assigned duties with precision.

• Full Telegram Integration — Your Agents on Your Messenger
  AgentBridge connects to Telegram as a user account (WTelegramClient, MTProto) and behaves like any other chat client: send a private message — text or files — and the agents reply in the same chat, including the documents they produce. Attachments are supported both ways, first login is guided from the TUI (verification code), an optional allow-list restricts who can talk to the agent, and the configuration lives in telegram.json (editable from the TUI, by hand, or with the guided setup scripts). See docs/telegram.md.

  

• AI‑Exoskeleton Technology for Enhanced Model Performance
  Our proprietary AI‑Exoskeleton framework significantly amplifies the capabilities of AI models while reducing bias in complex document processing. Just as an exoskeleton enables a human to lift weights far beyond natural limits, AI‑Exoskeleton empowers smaller models to outperform frontier‑scale systems in specific office workflows. It strengthens analytical consistency, improves the accuracy of business reports and technical documentation, and produces ready‑to‑use PDF outputs with exceptional reliability. This technology transforms artificial intelligence into a genuinely augmented professional tool capable of sustaining cognitive workloads that would normally require specialized human teams.

• True Application‑Level Sandbox — Agents Cannot Act Outside Their Tools
  Every agent operates inside a virtual workspace path that acts as a real sandbox: a limited action perimeter that no tool method can breach. The agent's only way to touch the world is through its tool methods — no shell, no OS API, no direct network, no filesystem access beyond what a tool explicitly exposes — so the perimeter is enforced structurally by code, not by prompt instructions that a crafted input could bypass. Competing systems either trust the prompt alone (defeatable by injection) or require expensive OS‑level sandboxes (chroot, Docker, VMs) that a common user cannot set up. Here the sandbox is application‑level and zero‑infrastructure, yet absolute: powerful inside its perimeter, harmless outside it.

• GDPR‑Ready Anonymization — Privacy by Design for External Providers
  A robust anonymization service protects personal data — names, keys and sensitive identifiers — before any request reaches an external LLM provider (Copilot, Gemini, ChatGPT, DeepSeek and more), and restores it seamlessly in the reply. It is enabled with a single switch, adds no perceptible latency to agentic interactions, and is completely transparent to the user: the agent keeps its full power while the machine never exposes what should stay private. This makes the platform a strong fit for the European market, where GDPR compliance is a hard requirement.

• Universal Tool System (UTS) — Tools That Run Natively, Not as Scripts
  Our Universal Tool System gives the AI its abilities through plugins that are compiled .NET assemblies the agent drives directly — no Python, no Node, no interpreter, and no framework stack to install. Deterministic intelligence (UISupportGeneric) reads the compiled code and builds the tool interface on the fly, exactly and without hallucination; the generative AI then picks and drives the right tool. The result is a faster, more responsive AI: tools run as native machine code — modern .NET compilers rival hand-tuned C/C++ — and are called in-process with zero overhead, with no interpreters, no HTTP and no serialization between the agent and its actions. The machine stays light, answers come back sooner, and the heaviest jobs finish faster — all inside a native application‑level sandbox (a structural action perimeter that no tool method can breach) that needs no chroot, Docker or VMs. Tools are universal — a single AnyCPU binary runs on Windows, Linux, macOS and iOS — and are installed by simply dropping a folder into Tools/, with hot‑add: new plugins are activated live, 30 seconds after they appear, without a restart. End‑user guide: Universal Tool System (UTS).

Your documents area: the company's brain and memory

Think of the documents area as your company's brain. It is a simple folder on disk — nothing special, just a place where your files already live. Whatever you put in it, the AI can read, remember and use: contracts, invoices, client files, product sheets, emails, spreadsheets, technical drawings... everything. It does not matter how much data you have or how big the files are: the more you store, the smarter your AI becomes, because it answers using your real documents, not guesses. You never upload anything into the chat — you just keep working with your normal folders, and the AI reaches into them directly.

How to configure the documents area

1. Open AgentBridge and type /modelsetup (menu File → Models & Providers).
2. In the General tab, set Documents path to the folder that holds your documents. The default is your personal Documents folder — you can change it at any time.
3. Press Save. AgentBridge starts reading that area in the background: the first indexing of a large archive takes a few minutes, but you can keep working while it runs.
4. From now on, ask the AI anything about your documents — it searches the whole area and answers from your data. If you move to a different folder, just change the path again: AgentBridge automatically re-indexes the new area.

How to configure the LLM provider and API keys

1. Open AgentBridge and type /modelsetup (menu File → Models & Providers).
2. In the LLM & Providers tab, pick the active provider; use Add… / Edit… to
   create or edit a provider. The provider dialog includes an API key field (masked on
   screen) — every cloud provider (DeepSeek, Z.ai, Gemini, Anthropic, …) needs its key;
   local providers (Ollama, ExLlamaV2, bridges on localhost/127.0.0.1) leave it empty.
3. Press Save. Keys are stored per-provider in providers.json next to the executable
   (the single source of truth, excluded from updates) — you can also edit that file
   directly. The manual (§3 — Configure the JSON files)
   documents every field.

Comparison with Main Alternative Products

What you can do with it

• Chat with AI agents from the terminal — streaming replies, @ file attachments,
  prompt history, sessions, all in a full-screen UI with a command palette.
• Multilingual UI — the terminal UI runs in the system language when supported
  (English, Italian, French, Spanish, German, Russian) and falls back to English otherwise;
  system messages from the orchestrator are localised too (see docs/TUI.md).
• Open the web GUI in one keystroke — /web (menu Web → GUI) downloads on first run
  and launches the Giraffe AI web client in the browser, already connected to this server.
• Expose the agents as a local OpenAI server — point any OpenAI client at
  http://localhost:5290/v1 and it drives the agents without modification (see the
  manual).
• Switch the LLM on the fly — DeepSeek, Z.ai, Gemini, Ollama, ExLlamaV2 and more, with
  a context-window guard that refuses an overflow and explains why.
• Per-provider agent interaction mode — each provider can drive the agent tools via the
  JSON tool-calling API (API) or the application CLI (CLI), or leave it Default (CLI
  for small models, API for large ones). Set it in the provider dialog under Models &
  Providers; the active mode is shown on the status page and reported by GET /v1/models
  as interaction_mode.
• Configure models & providers from the UI — /modelsetup (menu File → Models &
  Providers) adds, edits or removes providers, picks the active model, sets the
  per-provider API keys, SMTP/IMAP and documents path — no JSON editing required.
• Voice in the terminal — dictate from the server microphone (Windows) and hear the
  replies spoken by Kokoro neural TTS, in the UI and over the API.
• SIP telephony — the server becomes a phone endpoint: auto-answer behind a DTMF PIN
  (3 attempts, 24 h lockout), outgoing calls, and full voice conversations with the agents
  over RTP (whisper STT + Kokoro TTS). See docs/sip.md.
• Telegram chat — private-chat messaging with the agents, attachments both ways,
  allow-list access control and TUI-guided first login (WTelegramClient userbot).
  See docs/telegram.md.
• Upload-and-attach files — documents and images converted to Markdown server-side,
  attached to chat requests as file_ids.
• Agents with tools — web, search, research, Word, spreadsheet, email and multi-agent
  sets; pick the right tools per chat with /agent or the API model field.
• One conversation everywhere — messages from the terminal go through the exact same
  endpoint any client uses, so you can chat in the TUI while a script keeps driving the
  agents on the same port, simultaneously.

Quick start

Run the one-line install above — or download the archive for your platform from the
Releases page, extract and run
agent.exe / agent.
No .NET installation needed; each archive already includes the Kokoro TTS voices and model.

curl http://localhost:5290/health   # {"status":"healthy","timestamp":"..."}

The full step-by-step guide — installation, JSON configuration, the terminal UI and how a
client connects to localhost — is in the user manual.

Documentation

The user guides above (docs/) ship next to the executable in every release archive;
the developer guides (docs-dev/) stay in the repository only.

How it works

AIOrchestrator is a .NET library — it cannot run alone. AgentBridge hosts it and exposes
its chat pipeline as a standard web API. One process. Your machine. Your agents.

flowchart LR
    subgraph Clients["You — however you prefer"]
        A["Terminal UI<br/>(/agent chat)"]
        B["Any OpenAI client<br/>(SDKs, bots, scripts)"]
        C["Web GUI"]
    end
    subgraph Server["AgentBridge — one process on your machine"]
        API["OpenAI-compatible API"]
        AGENT["Your agents<br/>AgentHarness + tools"]
    end
    subgraph Models["Your models"]
        LOCAL["Local<br/>Ollama · ExLlamaV2<br/>DeepSeekBridge"]
        CLOUD["Cloud<br/>DeepSeek · Z.ai<br/>Gemini · Anthropic"]
    end
    A --> API
    B --> API
    C --> API
    API --> AGENT
    AGENT --> LOCAL
    AGENT --> CLOUD

The agents do the work — locally, under your control:

sequenceDiagram
    autonumber
    participant U as You (TUI / client)
    participant A as Agent (on your machine)
    participant T as Tools (web · search · docs · sheets · email)
    participant M as LLM (local or cloud)
    U->>A: "Analyse the market, draft the report"
    loop Agent loop — plan, act, verify
        A->>M: next step?
        M-->>A: call the web tool
        A->>T: gather the data
        T-->>A: sources found
        A->>M: reason over the result
    end
    A-->>U: PDF report ready

Your data stays yours. Agents run on your machine inside an application-level sandbox;
only the model call leaves it — and only when you pick a cloud provider. With local models,
nothing leaves at all.

Built on the AIOffice ecosystem ·
AgentBridge repository.