This page is for hosted and managed runtime lanes. If you want the one-time toolkit, the training vault, or the manual-first buy flow, use the offers page. If you want the proof stack first, use the demo hub.
Your AI does things you didn't ask it to. These plans cover the hosted and managed runtime side; the one-time package lane lives on the offers page.
In plain English. No jargon.
Problem: A customer asks your support bot about refund policy. The bot also reveals your internal pricing formula because a prompt injection was hidden in the conversation.
Solution: The pump profiles every query. When it detects a narrow tongue profile (only Cassisivadan/compute is active, everything else is null), it flags the input as suspicious before the model sees it.
Result: QUARANTINE. The suspicious query gets reviewed before reaching your model. No data leak.
Problem: Your medical Q&A bot starts giving legal advice. Your code assistant starts writing poetry. Domain drift happens silently and compounds.
Solution: The pump knows which tongues (domains) should be active for each task. If a code model's output has a creative writing tongue profile, something is wrong.
Result: The pump catches domain drift in real-time, before the wrong-domain output reaches your users.
Problem: Model A processes user input. Model B takes Model A's output and acts on it. A prompt injection in Model A's output cascades through the entire chain.
Solution: The pump runs TWICE per cycle -- once on input (orient), once on output (verify). If Model B's output has a completely different null pattern than Model A's input, cascade injection is detected.
Result: Cascade blocked. Each model in the chain is independently verified.
Problem: EU AI Act (Aug 2026) requires risk management, logging, and conformity assessment for high-risk AI systems. SOC 2 now includes AI governance controls. You're a 5-person team.
Solution: The pump generates audit logs automatically. Every query gets a timestamp, tongue profile, governance decision, and source reference. Export as JSONL for your auditor.
Result: Compliance documentation that writes itself. No security hire needed.
Total overhead: <10ms per query. Works with any model. No model changes required.
The pump catches the failures that make your customers lose trust. Domain drift, prompt injection, hallucination -- detected before your users see them. $49/mo is cheaper than one angry customer leaving.
Self-governing AI that audits itself. The pump runs on a $5/mo VPS. Your bookkeeping bot won't accidentally send customer emails. Your support bot won't reveal pricing data. The audit log satisfies your accountant.
Risk management, data governance, technical documentation, automatic logging, transparency, human oversight. The pump handles the AI-specific controls. You handle the rest. $499/mo vs $200K for a compliance platform.
See full benchmark methodology and reproducible results →
Prefer the one-time toolkit and training-vault lane instead? Open offers →
If you're evaluating this for a government or grant-funded project:
Phase I: ~$100K (6 months). Phase II: up to $400K (24 months). SCBE aligns with NIST AI RMF and Cybersecurity Framework. Post-quantum crypto (FIPS 203/204) is a priority area.
Grants for technology-based economic development in rural communities. SCBE is built in Port Angeles, WA (Olympic Peninsula). Rural tech that competes with Seattle.
Rural Investment for Small-business Empowerment. Connects rural businesses with solution providers and subject matter experts. Run by PNWER with WA Dept of Commerce funding.
No. The pump is middleware. It sits between your users and your model. Your model doesn't change. The pump just makes sure the input is safe and the output is on-domain before it reaches production.
Any model that accepts a system prompt. OpenAI, Anthropic Claude, Google Gemini, Meta Llama, Mistral, Qwen, local models via Ollama. The pump generates a text-based orientation packet -- no model-specific integration needed.
The core pump library is open source (MIT license). The SaaS adds hosted infrastructure, higher rate limits, output verification, cascade detection, and managed compliance reporting.
Six constructed languages (Kor'aelin, Avali, Runethic, Cassisivadan, Umbroth, Draumric) with 256 tokens each. They provide domain separation -- each tongue maps to a knowledge domain (Control, Transport, Policy, Compute, Security, Structure). The pump uses them to profile what domain a query belongs to and what domains are absent. It's like having six specialists look at every input instead of one generalist.
Most security systems look at what's present in an input. We also look at what's absent. When a prompt injection tries to sound like a normal query, it typically activates only 1-2 domains and leaves the other 4-5 completely silent. That silence IS the signal. Normal text doesn't leave 5 out of 6 domains empty.
Yes. The open-source library (pip install scbe-aethermoore) includes the full pump with tongue profiling and null-space detection. The hosted service lanes add scale, output verification, and compliance features, while the one-time package lane lives on the offers page.
Issac Davis, solo founder, Port Angeles, WA. Started as a DnD campaign on Everweave.ai, became 12,596 paragraphs of game logs, became a security framework, became a patent (USPTO #63/961,403), became this. ORCID: 0009-0002-3936-9369.
Start with the open-source install, move to the one-time toolkit and training-vault offers if you want the package lane, or use these hosted plans when you need runtime governance as a service.
SCBE-AETHERMOORE · Built by Issac Davis in Port Angeles, WA · Patent Pending USPTO #63/961,403
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