- Current version31 harnesses
- One version behind6 harnesses
- Edited locally3 harnesses
SalesSolutions EngineeringCustomer Success
Every prompt checked before it ran.
2 prompts stopped.
Enterprise Sales Harness
Zime hub Discovery skill, by harness Yesterday's use, by model Policy checks ActionTry it
Run every sales harness from one hub. Know what each one cost and produced.
The Enterprise Sales Harness is a governed runtime and central control plane. It sends approved judgment to each seller's harness, keeps every deployment current, and records what each use cost and produced.
# ai-platform
Sam9:41 AM
Which harnesses run an outdated discovery skill, and what did yesterday's use cost?
Zime hubAPP9:41 AM
Here are your harnesses, their versions, and what each costs.
1,200+
GTM behaviors
trained with 50K+ human-in-the-loop hours.
5 mins
to go live
with your GTM judgment, ready to drive adoption.
80%
of reps running behaviors
in 90 days, resulting in 20% uplift in deals won.
The Problem
Who governs the harnesses your reps and agents already run?
Every rep with an AI assistant now runs a harness of skills, prompts, and documents. Each one works for its owner. No one sees the set.
One harness per rep, and no owner.
Reps and teams build their own. Each one is managed as a one-off, or not at all.
Skills drift and go stale.
Someone copies a skill, edits it, and overwrites the original. The strategy changes. The harness does not.
Inference cost no one watches.
Models, tokens, and MCP calls run across many endpoints. The bill arrives after the fact.
Compliance claims with no evidence.
Prompts run without a policy check. Agents act without guardrails. Security asks for proof and gets assurances.
The Gap
An individual harness serves one user and drifts.
Most revenue stacks hold nothing that manages the set.
One harness
Serves one user. Drifts.
The enterprise needs
A managed way to deploy judgment, skills, workflows, and agents.
The Solution
Enterprise Sales Harness: one governed runtime for every harness
One hub sets policy, configuration, and releases. Each harness receives skills and documents, and you keep what you built. It runs and governs Behavior Graph for Sales, CRO Initiatives, and Programmatic Adoption.
Deploy
Manage every harness from one hub, and keep each one current.
- Central release, refresh, and retirement for every rep, team, and agent harness.
- Each harness receives skills, workspaces, and resource documents.
- Skills are tested, approved, versioned, and rolled back from the hub.
- No drift, and user-level flexibility stays in place.
- Private Deployment: Zime can run on hardware you control.
Hub and spokes
Connect
Connect the agents, systems, and tools you already run, with permissions intact.
- MCP connections to internal agents, customer-built agents and harnesses, and enterprise systems.
- Permission-aware access to CRM, call, account, and collaboration context.
- Central routing across agents, skills, data sources, and workflows.
- Delivery where sellers work: the CRM, Slack, or Microsoft Teams. No new tools.
- Four guardrail states, set by central policy. No harness sets its own.
Four guardrail states
Recommend · a person decides
Act · policy allows it
Escalate · hand to a manager
Request approval · pause until approved
Meter
Govern which model runs, and see cost as it accrues.
- Model selection, routing, and substitution by task, sensitivity, quality, and cost.
- Cost shown across inference endpoints, LLMs, and MCPs.
- Consumption attributed by team, workflow, initiative, agent, or user.
- Real-time view of what each agent does.
- Routing by sensitivity keeps sensitive tasks on the models you approve.
Cost, as it accrues
by teamby workflowby agentby user
Secure and trace
Check every prompt against policy, and trace every recommendation to its source.
- Central policy sets who can see what and who approves a behavior.
- Each prompt passes a policy and security check before it runs. The harness adds defenses against prompt injection.
- Role-based access controls and protected-information controls.
- Every recommendation traces to its source, its approver, and its version.
- Version history for skills, prompts, knowledge, workflows, and configurations.
Every answer, traced
Prompt · policy check passed
Access · role-based
Source · where it came from
Approver · who signed off
Version · which release
Business Case
Retire the one-off harness, and the cost that comes with it
Every one-off harness needs someone to update it, secure it, and explain it to an auditor. One governed runtime removes that work.
01
What success looks like
- Every harness current and consistent
- No outdated or divergent skills
- Cost visible as it accrues
- Every recommendation traceable
- Security questions answered with evidence
02
What it takes from you
- A named owner for the control plane
- Your MCP permission and security specs
- Monthly or quarterly freshness reviews
- A common baseline for AI use
Who is involved
Your team
- AI Platform Owner
- GTM Engineer
- RevOps
- Security Reviewer
Zime provides
- Forward-Deployed Engineer
Before and After
From one-off harnesses to one governed runtime
One-off harnesses
Copy→Edit→drift
- OwnershipEach rep owns one. No one owns the set.
- UpdatesCopied by hand, if at all
- Skill versionsUnknown
- Model choiceWhatever each rep picked
- CostSeen on the invoice
- Prompt checksNone
- AgentsAct as their builder allowed
- AuditAssurances
One governed runtime
Set→Deploy→Observe
- OwnershipA named owner at the hub
- UpdatesReleased, propagated, and rolled back from the hub
- Skill versionsVersioned, with history
- Model choiceRouted by task, sensitivity, and cost
- CostSeen as it accrues
- Prompt checksA policy check before each prompt runs
- AgentsFour guardrail states, set centrally
- AuditProvenance, approvals, and version history
Timeline
From inventory to scheduled reviews
- 1
Inventory
List harnesses, skills, agents, and endpoints. Name the owner.
- 2
Connect
Bring your MCP specs. Connect the CRM and chat tools.
- 3
Bring under the hub
Release versioned skills. Set guardrails and model routing.
- 4
Observe
Cost and agent actions appear as they accrue.
- 5
Stay current
Monthly or quarterly reviews. The hub propagates each update.
FAQ
Frequently Asked Questions
What is the Enterprise Sales Harness?
The Enterprise Sales Harness is the governed runtime and central control plane Zime provides for every rep, team, and agent harness. One hub sets policy, configuration, and releases. It keeps every deployment current and records what each use cost and produced.
How does a harness differ from the Enterprise Sales Harness?
A harness is one rep's, one team's, or one agent's working set of skills, prompts, and documents. It serves one user and drifts over time. The Enterprise Sales Harness manages every harness from one hub.
Does it replace the harnesses and agents a company has already built?
No. The company keeps what it built, and Zime keeps it current. The Enterprise Sales Harness connects to customer-built agents and harnesses through MCP and brings them under one control plane.
Which AI models does it work with?
It operates across models and does not depend on one. It selects, routes, and substitutes models by task, sensitivity, quality, and cost. It attributes consumption by team, workflow, initiative, agent, or user.
Can agents act without a person?
Central policy sets each agent to one of four states: recommend, act, escalate, or request approval. An agent acts alone only where policy allows that step without review. In a live deal, Zime guides and the person acts.
How does it handle security and audit?
Central policy governs who can see what and who approves a behavior. Each prompt passes a policy and security check before it runs. Each recommendation traces to its source, its approver, and its version.