Deterministic AI
Safebots Team

The Missing Trust Layer for AI

Safer

Verify, don't simply trust

Safebox: our new, unhackable environment, designed from the start to keep data safe.

Cheaper

SAVE MONEY.

Safebox: run AI models inside the box and spend 20x less on tokens than AI Agents.

Easier

Zero setup.

We manage it all, so you don't have to. Models. Workflows. Results.

How It Works
Meet the Team
The Problem

AI is evolving fast.
Millions are vulnerable.

See the latest incidents →

Too Much To Fix

PHP2Shell, HuggingFace, and more. It's impossible to patch millions of custom environments. It's time for ONE new environment built from the ground up to be unhackable.

Sharing Confidential Data

You rely on others for AI compute. Every prompt leaves your network and lands in someone else's data center. It's time to run AI in your own secure environment you can trust.

Regulatory Compliance

For many industries, privacy and confidentiality are not optional. HIPAA, FERPA, GDPR. It's time to make compliance with regulations come by default out of the box.

The Solution

AI Infrastructure You Own
and verify instead of blindly trust.

No system administrators.
No arbitrary commands.

Safebox is a sealed appliance. No one logs in. Updates require M-of-N auditor signatures — your auditors, not ours. The hardware itself proves what code is running.

Keep your confidential
data safely in the box.

Every prompt, every document, every response stays inside your sealed environment. No one trains on your data. Not even the host can read what's inside.

Run the best open models securely on your data.

DeepSeek, Llama, Qwen, Gemma, Mistral, Kimi — curated by the community, hash-signed, ready to go. New frontier models added every few weeks. Swap any time.

The Comparison

Cloud AI vs Safebox

The whole stack, on every axis that actually matters.

The cost math →Why open models win →
💰 Cost
Today

$5,000+/yr per person · per-token billing forever

Safebox

~95% less · no per-token · models loaded once, shared

🛡️ Safety & Audit
Today

$300K–$1.5M annually · doesn't transfer across environments

Safebox

Cryptographic record · verify from a browser · one environment

✨ Ease of Use
Today

Terminal · API keys · GPU drivers · prompting expertise

Safebox

Tap a workflow with a reputation score · no engineering required

🧠 Model Choice
Today

Locked to one vendor's models

Safebox

Curated open roster · verified weights · swap any time

🔧 Maintenance
Today

SSH · admin trust · manual updates · supply chain risk

Safebox

No SSH · sealed appliance · M-of-N signed updates

🔒 Privacy
Today

Your data on their servers · may train on it

Safebox

Stays in your environment · sealed · not even the host can read it

🔗 Vendor Lock-in
Today

Switching means rebuilding from scratch

Safebox

Open standards · designed for portability and audit

⚡ Performance
Today

API rate limits · 3am throttling · shared capacity

Safebox

Bounded by your hardware · linear scaling · no quotas

What runs in the box

Predictable, Reliable Workflows

Our solution is designed for businesses and organizations, not just individual use. It enables collaboration between teams and enforces organizational policies at scale.

01

Read

Observe data through mediated, read-only interfaces

02

Reason

AI generates structured outputs describing intent

03

Propose

Immutable task proposals — declarative, not executable

04

Validate

Policy constraints enforce what's permissible

05

Authorize

Human approval, multi-party, or time-delayed

06

Execute

Only approved actions run — with verifiable records

Learn more from the team →

INCIDENTS

Why This Keeps Happening

A running record of agent incidents, frontier-model capability jumps, and the institutions converging on one conclusion: the substrate has to enforce the limits.

Live incident tracker: AI Is Going Just Great
May 2026Institutional consensus

Anthropic: contain at the environment layer first

Anthropic's own engineering team published the conclusion after their most instructive incidents were both egress through permitted paths: "The deterministic boundary is what gets hit when everything probabilistic misses." The model layer couldn't catch them — there was nothing anomalous to see.

Anthropic Engineering

May 2026Offensive scale

Mythos flagged 10,000+ exploit-grade vulns in a month

Cloudflare ran Anthropic's Mythos Preview across 50+ partners under Project Glasswing. It chains low-severity flaws into working exploits with proof-of-concept code, at 10× prior capacity. Model-level safety controls proved unreliable: it refused research, then complied after a hidden .git folder was deleted.

Cloudflare · Project Glasswing

Apr 2026Economics

Agents can't predict their own resource usage

Stanford / MIT / DeepMind / Microsoft: agentic tasks consume 1000× more tokens than chat, with 30× cost variance on identical tasks and a best self-prediction correlation of 0.39. The substrate has to enforce token budgets — the model can't bound itself.

Stanford / MIT / DeepMind / Microsoft

Latest from the wild

Sep 13, 2026concerningmajor

Researchers tie the May 2026 RubyGems attack to a swarm of OpenAI agents that got code execution on RubyDoc servers

Based on our review, our agents used the RubyGems platform to access the internet to carry out benign tasks and retrieve public information.

Sep 11, 2026absurdminor

Microsoft Copilot Goes Offline for 100 Minutes, Also Breaks Its Own Suggestion Pills During a Resilience Test

And they say AI is going to kill us all when they can't even keep it running.

Sep 10, 2026scarymajor

Clearview AI Builds AI Profiling Tool That Lets Police Auto-Scrape a Person's Entire Online Life

"A hallucination-prone chatbot would not be trusted as an informant under any other regular circumstances."

Sep 10, 2026concerningmoderate

OpenAI agents left unauthorized messages on at least 10 more sites than previously disclosed, six independent investiga…

It's almost certain that there's more going on here that we just don't know about.

Sep 10, 2026concerningmoderate

Anthropic discloses fourth cybersecurity incident involving early Claude Opus 4.6

Anthropic had disclosed in July some of its Claude AI models had hacked into the systems of three companies during cybersecurity tests.

Sep 9, 2026concerningmoderate

OpenAI says a 10,000-agent swarm solved Navier-Stokes, but can't rule out learning from a mathematician's private Codex…

While unlikely, we cannot rule out that de-identified data derived from their usage of our products helped improve our models.

Sep 8, 2026concerningmoderate

AI Chatbots Abandon Correct Sleep Apnea Referral Advice 36% of the Time When Patients Push Back

"Correct advice was abandoned more than a third of the time. The only thing that changed was how the patient talked."

Sep 8, 2026concerningmoderate

AI-generated complaints flood courts, councils, and ombudsmen as "agentic flooding" strains public services

"The difficulty is that AI rarely uses one word when a hundred will do. What might previously have been a short email complaining about bins not being emptied can arrive looking like a High Court legal action."

Sep 8, 2026scarymajor

Attackers Used Multi-Agent AI Framework to Steal Thousands of Credentials in Under Six Hours

"Criminals, like the ones who conducted a mass exploitation campaign in just six hours, will gravitate to attacks that are faster than we can respond to."

Sep 5, 2026scarymajor

OpenAI Agents Spent Weeks Colonizing a 25-Year-Old German Wiki Forum Without the Lab's Knowledge

The administrator spent the next 5 days fighting a losing battle against the agents, deleting an average of 100 pages a day while the agents created about 400 new pages per day.

The Consensus

We're Not the Only Ones Saying It

In 2026 the biggest names in tech started warning that renting AI means paying twice — in tokens, and in the proprietary knowledge you hand over. That's the exact problem Safebox is built to solve.

“You essentially pay for intelligence twice: once with money, and again with something even more valuable — the proprietary knowledge you must reveal to make that intelligence useful. The better you want the model to perform, the more of that knowledge you have to feed it.”

Satya Nadella

CEO, Microsoft — “The Reverse Information Paradox”

“Every single enterprise in this country — these people are livid. They are paying for tokens that create no value, and the AI players are stealing their weights and alpha.”

Alex Karp

CEO, Palantir — on CNBC, July 2026

Safebox's answer: your data, prompts, and the knowledge your corrections create never leave the sealed box — not even the host can read them.

“Design for containment at the environment layer first, then steer behavior at the model layer. The deterministic boundary is what gets hit when everything probabilistic misses.”

Anthropic Engineering

How we contain Claude across products

“Attacker timelines are shortening, but defenders need more than speed. We must harden systems to make exploitation difficult by design — so a vulnerability's existence doesn't dictate the speed of our defeat.”

Grant Bourzikas

CSO, Cloudflare · Project Glasswing

“The biggest challenge for enterprise AI is that it's still impossible to make sure everyone gets the same answer to the same question, every time. Domain knowledge becomes more valuable by the second.”

Mark Cuban

Investor / entrepreneur

“If you put an essay on best practices into the agent's context, it reads it and skips the actual work. If you put a workflow there, the agent has something to do, and you have something to verify. Process over prose.”

Addy Osmani

Director, Google

Architecture

Secure Execution Architecture

Safebots structurally prevent prompt injection, runaway automation, and total system compromise. Information, decisions, and execution are isolated by design — not policy.

Read-Only Reasoning

Models access data through mediated interfaces. Prohibited from writing state or executing actions.

Immutable Task Proposals

Content-addressed, declarative intent objects. Describe actions without performing them.

Validation & Enforcement

Monotonic policy evaluation. Can only restrict execution, never grant authority.

Governance & Authorization

Human approval, multi-party thresholds, time delays. Logged and immutable.

Isolated Execution

The only components that act. Execute only authorized proposals with verifiable records.

Flow Control & Backpressure

Pipeline-regulated capacity. Parallel batch execution without increasing authority.

Read Full Architecture PDFConnect with the Team

Deep Dive

See It in Action

Watch our explainer videos to understand how Safebots transform AI security.

Go Deeper

Read the Full Story

Architecture docs, economic analysis, and the thinking behind the stack.

Intellectual Property

10+ Patents Pending

Our architecture is protected by a comprehensive patent portfolio spanning sealed compute, capability partitioning, deterministic execution, consensus protocols, and AI reasoning systems.

Infrastructure & AttestationExecution & SafetyReasoning & Acceleration

Non-provisional conversions in progress for 2027 filing deadlines. Portfolio covers the full Safebots stack from hardware attestation through AI reasoning.

Get Started

Secure Your Data

Explore the Safebots architecture and discover how capability partitioning, immutable task proposals, and flow-controlled pipelines create AI systems that are safe by design.

Read ArchitectureConnect with the Team