Welcome to
Razorglint Labs
Creators of the CTLM Sovereign AI Engine
Local-first AI for high-risk environments. CTLM runs on owned hardware, survives outages, and keeps a replayable memory of what happens – so defense, ports, and critical infrastructure can understand and recover from modern attacks.
What CTLM is
CTLM is a sovereign, local-first AI engine built for high-risk environments.
Instead of a stateless chatbot in the cloud, CTLM runs as a local node on owned hardware, with its own persistent memory and defensive architecture.
Its job is simple:
keep operations understandable and recoverable when systems are under cyber pressure or completely offline.
• Runs on your hardware – including air-gapped and low-connectivity environments.
• Replayable memory – CTLM keeps a reconstructable history of what it sees and does; more like an AI black box than a chat window.
• Defensive intent only – designed for continuity, incident support, and forensics – not for offensive operations.
Who we build CTLM for
CTLM is designed for teams who can’t outsource trust to a public cloud chatbot.
Defense & national security units that need sovereign, offline-capable AI support.
Ports & critical infrastructure operators under constant ransomware and outage risk.
Security-heavy enterprises (finance, healthcare, energy) that need evidence, not guesswork, after an incident.
What you can get from Razorglint today
Fixed-scope remote engagements to map what sovereign AI nodes like CTLM would look like inside your environment – and to design real pilots, not just slide decks.
Sovereign AI Readiness Snapshot
You get:
• One 60–90 minute remote workshop with technical and security stakeholders.
• A 4–7 page readiness memo covering:
• current state and constraints,
• 2–3 realistic sovereign AI use cases,
• a first CTLM pilot concept on your own hardware.
Available for security-heavy enterprises, ports, and infra operators.
Defense & Infrastructure Pilot Scoping
For defense, ports, and critical infrastructure operators who want something more concrete than a slide deck.
You get:
• Two focused remote sessions (discovery + review).
• An 8–12 page pilot scoping brief that defines:
• objectives and success criteria,
• target systems and data boundaries,
• suggested architecture for a CTLM node on owned hardware,
• risk and governance notes under your security rules.
This gives you a document you can walk into a strategy, security, or innovation meeting with.
CTLM Demo & Technical Briefing
CTLM Demo & Technical Briefing
A live walk-through of the CTLM engine, cockpit, and memory fabric on a local system.
Ideal for:
• CISOs, cyber leads, and innovation teams evaluating sovereign / offline AI.
• Investors and strategic partners who want to see how CTLM behaves with real sessions and incidents.
We tailor the session to your context and focus on concrete scenarios, not marketing slides.
CTLM Intent Engine v0.1 – AI vs AI defense
CTLM Intent Engine v0.1 – AI vs AI defense
The CTLM Intent Engine is our first focused demo module. It analyses sequences of prompts or actions and detects malicious or deceptive intent – even when each individual step looks harmless.
In a typical session, it can:
• track stepwise escalation (“security audit” → recon → exfiltration).
• assign a risk score (0–100, mapped to LOW / MEDIUM / HIGH).
• label primary / secondary intents (recon, exfiltration, automation, sabotage).
• generate a plain-language explanation of why a chain is dangerous and which steps raised the risk.
v0.1 is built for demos and pilot evaluations with cyber teams and investors who want to see semantic defense in action.
Real incidents today: ports offline, hospitals reverting to pen and paper, cities declaring emergencies after cyberattacks.
Why this matters now
Critical systems are being hit by ransomware, supply-chain attacks, and AI-assisted intrusion tactics. Ports have gone dark, hospitals have switched back to pen and paper, and cities have declared emergencies after cyber incidents.
Most AI tools don’t help in those moments. Cloud chatbots were never designed to:
• survive inside a compromised or disconnected network.
• keep a reliable memory of what happened.
• provide an evidence trail for investigators and commanders.
CTLM is built to close that gap:
• It runs as a local, sovereign node on owned hardware – even in offline or denied environments.
• It keeps a replayable memory of what it sees and does, so you can reconstruct incidents instead of guessing.
• It is designed as defensive infrastructure: a black box and backup brain for the people who still have to keep operating when everything else is failing.
RazorGlint Labs is operated by TCOG Collective (LLC, New Mexico, USA).
Principal office (LLC):
1209 Mountain Road Pl NE, Ste R
Albuquerque, NM 87110, USA
Mailing / suite address:
1621 Central Ave, Suite 8630
Cheyenne, WY 82001, USA
EIN: 38-4361759