AI Engineering, AI Security, AI Consulting, AI Strategy — done by the same senior practitioners, in any combination. We sell the work, not the slide deck about the work. Our security work runs as a ladder: low-friction entry offers — phishing programs, vendor risk assessment services, tabletop drills — that solve an obvious pain and grow into AI security consulting, virtual CISO for AI programs, and governance retainers. Our edge is the crossover: the same bench that builds your AI and data platforms secures them — access control, data observability, and governance, by the people who wrote the architecture.
Most teams come to us mid-problem, not shopping for a service. Pick the line that sounds like your week, and we'll point you at the fix, the proof it works, and something worth reading on the way.
We take pilots stuck in "almost works" and rebuild them as production systems — data foundations, a real deployment path, and a runbook your team can operate. You get working software on a fixed fee, not another proof of concept.
We build the test harness that proves whether your system works — a graded question set, the right quality metrics, and automated checks that block a bad change before it reaches users. You stop shipping on gut feel and start shipping on evidence.
We stress-test your LLM and agent system the way a real attacker would — prompt injection, tool abuse, data leaks across users — and hand back a prioritized list of what to fix before launch. Where it makes sense, that grows into ongoing security oversight.
We put the controls in place that auditors and regulators ask for — clear records of what the system did and why, who approved it, and what happens when something goes wrong. The result is evidence you can show, not a policy nobody follows.
We give you a short, honest read on where AI is actually worth it for your business, what to build first, and what to skip. You leave with a sequenced plan and a realistic budget — not a 60-slide deck.
The AI Security Snapshot Sprint is a fixed-fee, point-in-time threat model and adversarial test of one AI system — prompt injection, tool abuse, and data-leakage pathways, mapped to OWASP LLM Top 10 + MITRE ATLAS. You get severity-ranked findings with remediation and a runbook, from $18k. The cheapest way to know where it can be abused before an attacker does.
The AI Readiness Sprint is a four-to-six-week fixed-scope read on whether your business is actually ready to ship AI — a maturity scorecard across data, governance, infra, and talent, a shadow-AI audit, and a prioritized 90-day use-case roadmap, from $12k. Consultant-led AI projects succeed roughly 67% of the time versus ~33% for internal builds; this is how you land on the right side of that line before you spend the build budget.
A vCISO for AI Programs is retained senior security leadership on a fraction of a hire — owning the AI risk posture and governance cadence, reporting to your board and insurer, and keeping the red-team harness, RMF framework, and AI inventory current. From $6k/mo. High-value advisory with a runbook on exit — not a headcount you rent and not a 24/7 SOC.
We build and secure AI and data systems for government programs — the same senior team, working to your compliance and clearance requirements, with full ownership handed to you. Start with the capability brief.
Whatever service you buy, the engagement rails are identical: fixed scope, named team, weekly cadence, a runbook on the way out.
Not a staffing pyramid and not a slideware shop. A senior-only bench, open-source security IP we authored, and engagements that end in named deliverables you keep.
See mcp-warden on GitHub ↗RAG pipelines, agentic workflows, multi-tenant SaaS, inference infrastructure. We ship the service, the eval harness, the observability — and the runbook that outlives the engagement. AWS-native by default; bring-your-cloud on request.
Lean cadence, decision log, IP transfer. Customer-zero by week 11 is the standard story.
SBOM, model + dataset provenance, traceability matrices, ATO-friendly architecture diagrams. Cleared-staff on request.
PrivateStack is our multi-model platform for running AI on open-weight models like Llama and Mistral — deployed inside your own cloud or VPC, or hosted by us. Proprietary models (GPT, Claude, Gemini) stay on tap for the workloads that need them. We have built this end-to-end and run it in production; we can stand up the same pattern for you.
AI security consulting that runs as a ladder — start with a scoped, fast-to-approve entry offer and grow into AI risk assessment, red-teaming, an AI governance framework, and a virtual CISO for AI programs. Threat models adapted for LLM and agent systems. Findings with remediation, not a 60-page binder. Lean, high-value advisory — we do not run a 24/7 SOC or managed detection; we make your team and tooling defensible.
Buyers usually start on the security ladder below and grow into this work.
Mapped to your existing SOC 2 / ISO 27001 controls. Findings + remediation in plain language for engineering leadership.
NIST AI RMF mapped on every artifact. CMMC-aware delivery. Cleared-staff capable for sensitive engagements. ATO-friendly handoff.
Three tiers, one bench. Entry offers are scoped tight and priced for fast budget approval — they solve a visible problem and document due diligence. They also surface the work that pays off most: AI security, governance, and retained leadership.
The crossover between AI/data architecture and business information security — access control, data observability, and governance — handled by the people who wrote the architecture, not a separate audit team reading it cold.
No 24×7 managed detection, no MDR, no round-the-clock staffing. We make your team and tooling defensible and hand back a runbook — high-value advice, not a headcount you rent.
Readiness assessments, architecture reviews, build-vs-buy memos, fractional CDO/CAIO. The person reviewing your stack is the person who'd build it — not a partner with a deck to defend.
Recommendations sized to a quarter of headcount, with reversibility scores on every decision.
FAR-clause-aware recommendations. CMMC/FedRAMP impact on every memo. Vehicle-strategy alongside the build-vs-buy.
12-month roadmaps, operating-model design, investment theses, M&A due diligence. We model the ROI in numbers your CFO will defend and your board will sign — and we'll be back next quarter to revise them.
ROI/NPV with sensitivity bands. Reversibility on every initiative. We'll defend every number we wrote.
Mission-aligned strategy. Acceptable-use frameworks for public-facing AI. Vehicle and budget cycle realities baked into phasing.