One Governed Work Plane. Model-Agnostic. Your Data Stays Yours.

The Governed Work Plane the Enterprise Actually Needs

Every large enterprise is trying to figure out the same thing: how to give employees AI that is powerful enough to matter, safe enough to ship, and honest enough to audit. The answer is not another copilot bolted onto Office or Salesforce. It is a governed work plane — one place where humans, agents, and data operate under the same policies, permissions, and audit trail.

Herd is that plane. Model-agnostic, deployment-flexible, and designed for enterprises that cannot afford to hand their data or their workflows to a single AI vendor.

One governed work plane. Model-agnostic. Deployment-flexible. Your data stays yours.

Why the Current Approach Isn’t Working

The enterprise AI experiment of 2024–2026 gave us three lessons the hard way.

• Point AI on top of point tools does not scale. Every SaaS vendor is shipping their own copilot with their own model, their own data policy, and their own audit story. There is no coherent governance, no unified observability, and no way to prevent capability sprawl.
• Model lock-in is the new vendor lock-in. Enterprises that bet on one AI provider in 2024 are already paying the price on cost, capability, and risk. Model-agnostic is not a nice-to-have — it is a survival requirement.
• Data leakage is a board-level risk. Every workflow that hands data to a third-party model is a compliance, privacy, and IP exposure. That risk compounds every quarter you delay.

What Herd Gives You That No Copilot Can

Herd is a substrate, not a feature. It is the layer that makes AI safe to deploy at enterprise scale.

Model-agnostic by design

Route any workflow to any model — frontier, open-weight, or private. Change models without changing workflows. Benchmark, A/B, and switch on your timeline, not the vendor’s.

Data stays where you put it

VPC, private cloud, or air-gapped deployment. Your data never trains anyone’s model. Your prompts never leave your perimeter. Full residency and sovereignty controls.

One audit trail for humans and agents

Every action — human or agent — is logged, attributable, and reversible. SOC 2 Type II, ISO 27001, and the audit posture your compliance team actually wants.

Governed by policy, not by prompt

Permissions, data classifications, and use policies enforced at the platform level. Agents cannot exceed the permissions of the human they act on behalf of. Ever.

How Transformation Leaders Deploy Herd

The pattern that works is deliberate: pick two or three high-signal workflows in a single business unit, deploy Herd as the governed substrate underneath them, and prove the model.

• Phase 1 (weeks 1–6): Deploy Herd in a controlled tenancy. Onboard one team. Migrate two workflows. Establish the audit and governance baseline.
• Phase 2 (weeks 7–16): Expand to the rest of the BU. Add agent workflows for the highest-value use cases. Retire the first tranche of point AI tools.
• Phase 3 (quarters 2–4): Scale across BUs. Establish Herd as the enterprise standard for AI-enabled work.

You are not buying a tool. You are building an operating capability that compounds every quarter.

Who This Is For

This is for Chief Digital Officers, Chief Transformation Officers, and enterprise architects at Fortune 1000 and Global 2000 companies who are accountable for making AI work at scale — safely, defensibly, and without betting the company on a single model provider.

• You have a mandate from the board or CEO to make AI work across the enterprise.
• You have compliance, security, and legal seats at the table that need to approve every deployment.
• You care more about optionality and governance than about the latest copilot demo.