AI safety shouldn't cost the Earth. We built the Natural Intelligence (NI) Stack because the status quo — running massively wasteful Guardian LLMs to police production LLMs — is an environmental crime, a compliance failure, and a business liability all at once.
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Using one massive neural network (a "Guardian LLM") to police another is brute-force, unreliable, and environmentally disastrous. Every successful prompt injection forces a GPU to burn energy generating a harmful output.
Worse, a regulatory tsunami is coming. The EU AI Act enforces fines up to €35 Million by 2026 for failing to govern your AI risk. You cannot afford a "black box" safety system.
Destill's NI-Stack is a deterministic, 108-agent cascade that intercepts threats before they hit your LLM. Because it uses branching logic and semantic hashes, it runs entirely on CPU (or optional NPU). Zero GPU required.
It's completely LLM Agnostic and Device Agnostic. By stopping attacks at the gate and compressing valid tokens, we literally save the planet's energy while securing your data.
Translate complex 12D AI safety into the vocabulary your C-Suite already understands.
The EU AI Act is imminent. NIST AI 800-2 is active. POAW (Proof of Agent Work) generates automated, cryptographic receipts for every AI decision. We turn legal liability into mathematical certainty.
Without verifiable metrics, AI deployments are uninsurable risks. NI-Shield provides underwriters with Munich Re aiSure™ aligned telemetry data. When you can prove your AI safety with 12-Sigma accuracy, your insurance premiums drop.
AEGIS protects the input. SIREN monitors the output feedback loop. QFAI-C compresses the hidden states to save 38% on token costs. It's a self-improving firewall that pays for itself.
Most LLM safety systems fail outside English. They train on ~15 languages and pray attackers don't use Yoruba, Cherokee, or Maori. We don't translate. We measure physics.
Competitors train dictionaries for 15 languages and call it "multilingual."
We measure the mathematics of attack patterns — entropy spikes, script anomalies, structural complexity, drift velocity. These signals are universal. Like detecting fire by measuring heat, not by recognizing the word "fire" in every language.
Destill.ai doesn't just block prompt injections; we prevent arbitrary GPU cycles from ever spinning up. At scale, this represents a massive reduction in the carbon footprint of global AI.
