Capabilities
Build it. Run it. Secure it.
Three disciplines, one team, zero handoffs. The people who design your stack are the people who operate it — and the people who attack it.
I — AI Infrastructure
Agents that ship. Then keep shipping.
Most mid-market AI projects die between the demo and the deployment — no architecture, no guardrails, no plan for the day the agent gets something wrong. We design and deploy agent systems wired into your actual workflows, with logging, permissions, and human escalation from the first run.
- /01Agent System Design & Deployment
Production agents built around your workflows, your data, and your risk tolerance — scoped permissions, audit trails, kill switches included.
- /02AI Readiness & Architecture Assessment
A blunt audit of your data, tooling, and processes: what’s automatable now, what isn’t, and what it costs to close the gap.
- /03Workflow Automation Engineering
Orchestration pipelines and integrations that connect your agents to the systems where work actually happens.
Proof
The typical mid-market AI initiative spends 9–18 months in pilot and never reaches production. Our standard: a working agent in your environment — touching real data, doing real work — inside 60 days, with rollback and a full audit trail from day one.II — Managed AI Operations
Deployment is day zero. We run the other 364.
An unmonitored agent doesn’t fail loudly — it drifts quietly. Wrong outputs, silent errors, permissions creep, costs climbing while quality decays. We operate your AI stack as a managed service, so it’s still trustworthy in month twelve, not just at launch.
- /01Agent Monitoring & Observability
Real-time visibility into what your agents are doing, what they’re costing, and where they’re going off-script.
- /02Evaluation & Drift Management
Continuous testing against ground truth, so quality degradation gets caught by us — not by your customers.
- /03AI Incident Response & Tuning
When an agent misbehaves, we triage, contain, root-cause, and fix — with a paper trail you can show an auditor.
Proof
Ask any team running agents in production what their failure rate was in month one versus month six. If they can’t answer, nothing is measuring it. Every system we operate ships with evaluation baselines on day one — so “is it still working?” is a dashboard, not a debate.III — Agentic Security
Your agents are an attack surface. Ours are the red team.
Every agent you deploy is a new identity with credentials, tool access, and an instruction channel an attacker can reach. We secure AI systems against prompt injection, data exfiltration, and tool abuse — and we run agentic security tooling for assessment and detection that a lean team could never staff manually.
- /01AI Red Teaming & Hardening
Adversarial testing of your agents and LLM applications — prompt injection, jailbreaks, tool abuse, data leakage — then fixing what we find.
- /02Agentic Security Assessments
Attack-surface mapping and continuous vulnerability discovery driven by automated recon and scanning swarms. A live, prioritized fix list — not a 90-page PDF.
- /03Detection & Response Buildout
Monitoring tuned to signal over noise across traditional infrastructure and your AI stack, with runbooks a human can actually execute.
Proof
In our lab, a coordinated swarm of specialized security agents covers reconnaissance, vulnerability scanning, and privilege-escalation testing across an environment in hours — work that takes a manual team weeks. That’s the asymmetry attackers already exploit. We put it on your side of the wall.Manifesto
The Dark Lantern
A dark lantern is an old tool — a flame with a shutter on it. Light exactly where you need it. Darkness everywhere else. Watchmen carried them. So did thieves. The tool didn’t care; it just worked. That’s the standard we build to — and the dual nature is the point. You can’t secure agentic systems unless you know how to attack them.
We started Dark Lantern Labs because we watched the same failure on repeat: companies bolting AI onto their business with no one responsible for running it and no one thinking about what it exposes. The pilot demos beautifully. It ships, barely. Then it drifts, leaks, or gets manipulated — and there’s no monitoring, no evaluation, no security model. Not a technology failure. An operations failure.
We’ve been the operators. We’ve run the tooling, chased the alerts, built the agent swarms, and broken AI systems on purpose to learn how they break by accident. So we build differently: small surface area, scoped permissions, real observability, and no component we wouldn’t want to be paged for. If we wouldn’t run it ourselves, we don’t deploy it for you.
We’re not a big-box IT shop, and we’re not trying to become one. We take a small number of clients and go deep — design through deployment through operations through adversarial testing. You’ll talk to the people doing the work, because the people doing the work are the firm.
Black and white isn’t just our palette. It’s the operating principle. Either the agent is monitored or it’s a liability. Either the alert matters or it shouldn’t exist. Either we’d stake our name on the build or we don’t ship it. There’s no gray zone in production.
Operating standards
How we hold ourselves to account
Contact
Bring us the agent nobody’s watching.
The pilot that stalled. The deployment running blind. The AI system no one has ever tried to break. Thirty minutes, no deck, no discovery-call theater — just a straight read on what’s exposed and what it takes to fix it.
We’re ready to build. The question is whether you are.
We take on a limited number of clients per quarter because every engagement gets the full bench — design, operations, and offensive testing. If you’re done with pilots, unmonitored deployments, and vendors who vanish after the SOW, this is the conversation you’ve been putting off.
Claim your slot