Demo a compliance-friendly multi-agent stack with a signed audit trail
Route different task types to MiniMax, DeepSeek, Kimi, or Llama 3.3 70B automatically
Reject prompt injection and jailbreak attempts before they reach the planner
Pull live Kraken or Vultr API data through agent tool calls
Runs in mock mode without keys, but full features need Speechmatics, Gemini, Featherless, Kraken, and Vultr credentials.
ATLAS is a hackathon project submitted to the Milan AI Week Hackathon 2026. It is a multi-agent system, meaning it strings several AI components together into one pipeline, and its main selling point is that every step in that pipeline is checked, logged, and cryptographically signed so that an enterprise could later inspect what the system actually did. The flow starts with voice input that is transcribed by Speechmatics. The text then passes through a layer called SOUF AI DPI, which inspects the prompt for things like jailbreak attempts, hidden instructions, base64 tricks, or unusual unicode characters. If the prompt looks adversarial, it is rejected with a 403 response and a regulation citation. Otherwise it moves on to a Gemini 2.0 Flash model that acts as the planner and breaks the request into smaller subtasks. Each subtask is then handed to a router that picks an open source model from Featherless based on what kind of work is needed. Agent style tool use goes to MiniMax, code work goes to DeepSeek, long context and multilingual work goes to Kimi, and general questions go to Llama 3.3 70B. The chosen model can call tools, which in this project include DuckDuckGo search, a read only sandbox database, the Kraken API for live crypto market data, and the Vultr API for infrastructure queries. Every action the system takes, from the initial prompt check through tool calls and the final answer, is recorded into an audit log. Each entry is signed with an Ed25519 key and chained to the previous entry with a SHA-256 hash, so changing any earlier record breaks the chain. Gemini also produces a final synthesized answer at the end of the pipeline. The README explains how to run it. A pip install plus a streamlit command launches the user interface, and the system works in mock mode without any API keys, which is useful for demos. There is a test suite the author reports as 29 out of 29 passing, a short video walkthrough, a pitch deck, and a project structure listing the modules for the gateway, orchestrator, router, tools, audit chain, and frontend. The license is MIT.
Generated 2026-05-22 · Model: sonnet-4-6 · Verify against the repo before relying on details.