Behavioral simulation built from your actual deals, your buyers, your playbook — not approximations. Every rep walks in ready.
90–120 day ramps eliminated
$0 margin for error in enterprise deals
5+ pilots in motion
Scroll
0–0
Day ramp times draining revenue before a rep closes anything
$0
Margin for error in complex multi-stakeholder enterprise deals
0+
Enterprise pilots in motion — structured scope, defined outcomes
The Problem
Enterprise deals are lost before the first real call
Training prepares reps for knowledge. Deals require performance under pressure — and those are two very different things.
01
Inadequate Training
Reps train through roleplay and shadowing — not real pressure scenarios. When the live call comes, they improvise.
02
90–120 Day Ramps
Long ramp times drain revenue capacity and add cost before a rep closes anything. The clock runs from day one.
03
Ungoverned AI Use
Every rep uses AI differently — or not at all. Inconsistent inputs produce inconsistent deals and lost revenue at scale.
The Solution
Consistency before execution — not after
01
Run Real Scenarios
Simulations built from your actual deals, your messaging, your buyer dynamics — not generic approximations.
02
Face Real Pressure
Objections, stakeholder pushback, deal complexity — all in advance. The pressure is real. The stakes are not yet.
03
Execute with Confidence
Every rep runs the same tested playbook. No improvising. No inconsistency. No revenue left on the table.
Governed simulation platform
Felt like speaking with an actual IT Director
"Better than Second Nature AI roleplays"
"The pressure was difficult but not impossible"
"I love it — it's been a crutch for me"
Why SimOS
Not generic roleplay Your actual deal pressure
Generic AI Roleplay
✕Hypothetical scenarios disconnected from real deals
✕Generic buyer personas that don't reflect your buyers
✕No connection to your messaging or playbook
✕Approximations of pressure — not the real thing
✕Every rep uses it differently — no governance
Governed Simulation
→Your real deal scenarios built from actual pipeline
→Your actual customers, stakeholders, and objections
→Your messaging and positioning — consistent and tested
→The actual pressure of your deals — measurable delta
→Every rep runs the same playbook — governance-native
Ready to govern your sales performance?
Services
This isn't software you configure It's an outcome you deploy
A GTM performance service delivered through a governed AI simulation platform — built around your deals, not a template.
◈
Custom Deal Simulations
Built from your actual pipeline, buyer dynamics, and messaging — not approximations. Reps practice exactly what they'll face.
Built from your real pipeline scenarios
Stakeholder-specific persona simulation
Objection mapping from actual deal history
MEDDIC and structured framework alignment
⊞
Governed AI Playbooks
Every rep runs the same tested approach. Your messaging is locked in before anyone picks up the phone. The AI doesn't wander.
Standardized messaging across all reps
Governance constitution and trust layer
Consistent positioning rep to rep
Onboarding and ramp acceleration
△
Performance Delta Measurement
Measurable improvement in simulated vs baseline — reported to CRO and RevOps before the subscription converts.
Baseline performance capture
Simulated scenario scoring
Delta reporting for CRO and RevOps
Pilot-to-expansion success metrics
The Motion
Repeatable entry Not a one-off sale
01
Trigger Event
A missed deal or ramp delay surfaces. The CRO feels it. RevOps owns it.
02
Pilot Entry
5–10 reps. Defined scope. Clear success metric agreed upfront. Low friction, high signal.
03
Prove the Delta
Rep performance in simulated vs baseline. Readiness first — win rate follows.
04
Team Expansion
Proven delta leads to full rollout. Subscription converts. Revenue impact compounds.
Built for teams running MEDDIC or similar frameworks
Pricing
Start with a pilot Prove the delta Then expand
No long-term commitment up front — entry is a defined-scope pilot with a clear success metric agreed before day one.
Pilot
Entry
Defined scope. 5–10 reps. A clear success metric agreed upfront. Low friction entry.
Contact Us
Pilot pricing based on team size and scenario complexity — pre-revenue rates available.
→5–10 rep pilot scope
→Custom deal scenario build
→Baseline and delta measurement
→RevOps and CRO reporting
→Success metric defined upfront
Most Common
Team
Full Deployment
Proven delta from pilot — full team rollout. Annual subscription. The standard becomes the standard.
$30K–$100K
ACV target range — final pricing based on team size, scenario complexity, and usage structure.
→Full team simulation library
→Governed AI playbook deployment
→Ongoing scenario refresh
→Performance delta tracking
→RevOps and enablement integration
→Quarterly business review
Enterprise
Custom
Multi-team, multi-org, or platform deployments — custom structure, custom scope.
Let's Talk
VAR and MSP teams, channel partners, and broader readiness programs handled on a custom basis.
→Multi-team deployment
→Channel partner programs
→Custom governance architecture
→White-glove implementation
→Executive-level reporting
SimOS is pre-revenue and currently onboarding founding pilot customers. Pilot pricing is structured to be low-risk with a defined outcome — not an open-ended commitment. If you're running a MEDDIC-style framework with 10–50 reps and feeling the cost of inconsistency, this was built for you.
Get In Touch
Schedule a pilot conversation
No pitch deck required — tell us where you're feeling the gap and we'll tell you if we can close it.
About
Built from real deal failure patterns
SimOS didn't come from a whiteboard — it came from 25 years of watching reps lose deals they should have won, and understanding exactly why.
C
Doug Chase
Founder and Architect · Chase Transform LLC
25+
Years Enterprise Sales
∞
President's Club
25+ years in enterprise technology sales, including global training roles and multiple President's Club recognitions. Constraint-first, governance-native architecture built from actual deal failure — not theory.
"AI doesn't tell me what truth is — I tell AI what truth is."
We built SimOS because generic roleplay doesn't prepare reps for the real pressure of enterprise deals
Every feature was designed from actual deal failure — not approximations, not thought experiments. Real lost deals, real missed moments, real reps who knew the product but weren't ready for that specific buyer in that specific situation.
Most sales training optimizes for knowledge transfer. SimOS optimizes for performance under pressure — a fundamentally different problem that requires a fundamentally different solution.
The AI governance layer isn't a feature — it's the architecture. When every rep runs the same tested playbook, the output doesn't drift. The standard holds. Revenue follows consistency.
Pre-revenue seed stage · 2025 · Chicago
The Architecture
Why governed simulation is a different category
Constraint-First Design
SimOS was designed around the constraints of enterprise deals — not simplified to fit a generic AI roleplay pattern. Every simulation is bounded by real deal dynamics.
Governance-Native Architecture
The AI layer is governed by a trust admission pipeline and governance constitution. Output drift is structurally prevented — not managed after the fact.
Domain-Native Build
This wasn't built by engineers who learned enterprise sales. It was built by a practitioner who learned to architect AI systems. That inversion matters.
Measurable from Day One
Success metrics are defined upfront — not reverse-engineered after deployment. The pilot structure exists because we believe in proof before subscription.
