Controlled AI work. Not chaotic AI output.
GW Slate™ creates governed outcome rails for AI-assisted teams — connecting approved context, workflow tools, human authority, policy gates, and proof before AI work becomes business truth.
Drafts live in one tool. Context lives somewhere else. Approvals happen in a separate channel. GW Slate™ gives the work a governed rail so teams can move faster without becoming generic, leaky, or untraceable.
Start with one workflow, one measurable outcome, and one proof trail. The demo setup adapts to your pain instead of forcing a platform tour.
For AI workflow builders, agencies, and automation teams that need policy gates, approval, and receipts around existing tools.
For proposal, campaign, content, localization, and market-adaptation workflows that need approved brand memory and human authority.
For teams deploying AI agents that need identity-bound execution, policy-scoped tools, kill-switch posture, and audit packets.
For regulated, published, or material workflows where every action needs proof objects, exportable evidence, and verification.
A buyer-visible black-box recorder for governed AI work. Demo data is clearly marked preview-only until the receipt core confirms canonical truth.
Client-style request enters the selected rail.
Approved corpus pack selected; raw proprietary memory remains controlled.
Source mode, egress, locale, reuse, and materiality rules are evaluated.
Output is created inside approved constraints.
Proof bundle prepared with hashes, policy decision, runtime path, and evidence references.
This isn't a product tour — it's a personalized scoping session. Tell us the workflow you want to govern first and we'll configure the rail, the proof trail, and the approval surface around your actual use case before we meet.
Pick one workflow. We bind policy, route the model, set the approval surface, grade the outcome, and seal the receipt.