What is WonderWave's private AI pilot?
It is a scoped implementation around one sensitive workflow. WonderWave maps the local boundary, configures Sentinel rules, builds a bounded bot workflow, routes model work through approved paths, and leaves reviewable evidence.
What is Velociti?
Velociti is the platform layer WonderWave uses to frame governed AI operations: Sentinel authority, bot coordination, local model routing, runtime visibility, chat-connected workflows, and audit evidence.
What is Sentinel?
Sentinel is the control authority for bots. It reviews requests against rules you set, including purpose, target system, duration, allowed tools, denied actions, network route, filesystem access, and approval owner.
Does sensitive workflow data leave our local environment?
The private pilot path is designed so sensitive workflow data, prompts, logs, model outputs, and evidence stay inside the approved local or customer-controlled environment.
Do hosted models receive our sensitive data?
For the private workflow path, the site and demo describe a local model route with hosted model API upload blocked for sensitive work. Any model route is written into the scope before implementation.
What do you need from our team?
WonderWave typically needs a workflow owner, current software stack, target systems, sample or redacted examples, approval owner, known risk points, and a description of what the team wants the workflow to produce.
How much internal time should we expect?
A focused pilot usually starts with a small group: an operational owner, an IT or systems owner, and the person who approves final workflow outputs. The review is easier when examples and current-process notes are ready.
What stays human?
Risky actions, final decisions, exports, policy exceptions, low-confidence outputs, and professional judgment remain with named reviewers. The pilot can draft, classify, summarize, search, and prepare evidence for review.
Can this work with our existing systems?
The pilot is scoped around existing tools and approved sources where possible: folders, documents, chat surfaces, repositories, runtime systems, records, and workflow outputs your team already uses.
What artifacts do we receive?
Common artifacts include a Sentinel authority map, workflow prototype, local model route notes, runtime probe report, evidence package, review checklist, audit trail, and rollout recommendation.
How is accuracy improved after launch?
The pilot records misses, low-confidence fields, reviewer edits, source gaps, and policy exceptions. Those logs help refine source selection, prompts, model choice, bot scope, and approval thresholds.
What happens after the pilot?
The team reviews the evidence and decides whether to expand, revise, pause, or move into governance support for additional workflows, model routes, bot scopes, and operating cadence.