Most companies don't have an AI problem. They have a shadow AI problem. SimOS gives every team a governed workspace — not a blank canvas.
Employees are already using ChatGPT, Claude, Copilot, and other AI tools without any oversight. Shadow AI isn't the exception anymore. It's the default.
Sensitive documents uploaded to public AI tools without controls
Outputs vary by who's prompting — no consistency across the team
Business processes drift from person to person
Off-scope guidance creates liability exposure
Managers have no visibility into how AI is being used
"Generic AI gives every employee a blank canvas. Businesses need controlled execution."
AI becomes risky when every employee uses it differently. SimOS solves it at the workspace level — not with policies, not with training, with governed systems.
No AI department needed. No six-month implementation. One workspace at a time.
We identify the workspace where AI inconsistency is costing you time, risk, or rework. One process. One risk surface. Clear scope before we build anything.
We build a governed AI sim bounded by your role definitions, process logic, policy layer, and output standard. Your rules. Your boundaries. Not a generic chatbot.
Via GPT Link (same day) or GT Edge AI (secure, multi-user, audited). No training maze. No AI background required. Consistent output from day one.
Generic AI tools depend on employees knowing what to ask, how to ask it, and how to verify the output. SimOS gives teams controlled AI workspaces built for consistency, oversight, and repeatable execution.
10 core sims. Standardized deployments. Fast to configure. Immediate relevance. Each sim independently deployable — stack for deeper coverage.
Train teams inside controlled AI workspaces built around your sales methodology, messaging standards, objection handling, and operational process.
Governed sales process sim — pipeline stages, objection handling, and messaging discipline enforced at rep level.
Role-specific behavioral onboarding. New hire enters a governed simulation of their actual job — not an LMS checklist.
Scenario-based simulation for sales calls, client escalations, or difficult internal conversations.
Governed decision support for legal practice. Matter intake, conflict screening, and practice-area triage — grounded in firm-specific ethical constraints and matter governance.
Policy-grounded guidance for employee incidents, complaints, investigations. Documented, consistent, defensible.
SMB internal audit simulation — financial controls, compliance checkpoints, and process risk surface mapped to org structure.
Standardizes how work gets done across roles. Governed decision trees, escalation paths, output quality thresholds.
Governed hiring simulation — interview structure, role-fit scoring, and decision consistency. Reduces costly mis-hires.
ICP alignment, messaging governance, and campaign brief simulation. Enforces brand voice and positioning consistency.
Tell us the workspace, the role, and the risk surface. Delivered in 48–72 hours. Same governed architecture.
There's no self-serve tier. We talk through your workspace, your risk surface, and what a governed AI deployment actually looks like for your team — then scope it together.
Pick a time that works for you. No pitch deck required — we'll talk through where AI inconsistency is costing you and which workspace fits.
A three-stage engagement — find the time drain, build the fix, keep it tuned. Grounded in your org's constraints from the first conversation.
No pricing displayed except the diagnostic rate below — everything past that is scoped to what we find.
We map your workflows to find where AI delivers real time-back — not theoretical automation, the specific tasks eating hours. Bounded timeframe, output: a prioritized list of what to build first.
We design and build the workspace around the highest-friction tasks — intake, drafting, research, internal Q&A — grounded in your org's constraints and compliance surface. Scoped to your workflows, owned by you when we're done.
Workflows change, teams turn over, new tasks emerge. We keep the system tuned to where the productivity gains actually are — session logging, drift monitoring, periodic review.
Decades of enterprise go-to-market experience, turned toward a governance-first approach to AI.
SimOS didn't come from a whiteboard. It came from watching teams lose time, money, and credibility because AI outputs couldn't be trusted to stay on track.
Every sim was designed from actual operational failure. Not approximations, not thought experiments. Real inconsistency, real liability exposure, real teams who had the tools but no governance layer around how they were used.
Most AI implementations optimize for capability. SimOS optimizes for repeatability — a fundamentally different problem that requires a fundamentally different solution.
The governance layer isn't a feature. It's the architecture. When every team member operates from the same bounded AI, the output doesn't drift. The standard holds. Results follow consistency.
SimOS was designed around the constraints of real business workspaces — not simplified to fit a generic AI roleplay pattern. Every sim is bounded by actual role dynamics.
The AI layer is governed by a trust admission pipeline and governance constitution. Output drift is structurally prevented — not managed after the fact.
This wasn't built by engineers who learned business operations. It was built by a practitioner who learned to architect AI systems. That inversion matters.
Success metrics are defined upfront — not reverse-engineered after deployment. The pilot structure exists because we believe in proof before subscription.
Contact me directly and we'll talk it through.
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