Governed AI for critical physical work
Holovast turns approved knowledge into governed workflows, adapts guidance per worker, and holds critical work to evidence, so deviations can be corrected in the moment, not at inspection, and governed work carries audit-ready proof.
The same control is extending from browser, tablet, and AR to physical AI agents.Five UK patent applications filed in 2026
All five applications are pending.
News highlights
Programmes, memberships and awards
External recognition and grant wins that support our focus on manufacturing execution.
1 min read
Holovast is a member of the NVIDIA Inception program, supporting our development of governed AI for critical physical work.
By Holovast Media • 5 Aug 2026
2 min read
Highlights from the Global Incubator Program's second market visit, from the Niagara region and the N3 Summit to the MaRS and Innovate UK Manufacturing Disruptor Showcase.
By Holovast Media • 7 Apr 2026
2 min read
Highlights from the Innovate UK GBIP: AI Enhanced Manufacturing mission, from the Manufacturing IT/OT Summit and MIT in Boston to Mill 19 and the ARM Institute in Pittsburgh.
By Holovast Media • 3 Apr 2026
Technology provenance & external references
All references
Innovate UK Smart Grant provenance (ARVAST R&D)
Holovast traces its technical foundation to ARVAST Smart Grant R&D and related public commercialisation announcements.
AI Skills Hub publication
The BridgeAI AI Skills Hub, delivered by PwC, publishes the ARVAST case study on AI-enabled on-the-job learning. Access is members-only and requires sign-in
Evidence-gated execution for physical work
Holovast governs what AI may instruct, what a person or agent may act on, what evidence is required, and whether physical work may proceed. Nothing skips the gate.
Govern approved sources
Propose cited workflow steps
Review and approve a version
Publish to the permitted audience
Assign and run through browser, tablet, or AR
Capture step-scoped evidence
Release, hold, or correct according to policy
Preserve the audit trail and review improvements
Physical AI direction
Holovast is exploring how the same evidence-gated control could govern robots and cobots within approved, auditable bounds.
What you get
What this means for your factory
Outcomes your team can feel on the line, and the measures they move.
New hires line-ready sooner
Structured onboarding and learning paths take new starters from first day to signed-off, without weeks of shadowing.
Right first time, more often
Workers see exactly how to do the job at the point of work, so critical steps are done correctly the first time.
Every worker guided at their level
Guidance adapts to each person’s experience, so learners are never lost and experts are never slowed down.
Defects caught as they happen
Deviations can be corrected in the moment, not discovered at final inspection after the cost is already sunk.
Answers without hunting
Workers can ask and get answers grounded in your approved knowledge, with sources shown, instead of chasing whoever knows.
Compliance without paperwork
Proof of how work was done builds itself as the work happens, audit-ready the moment anyone asks for it.
Start where you are
Three ways to take the next step: explore the platform in depth, enter through the funded FliT programme if you are a London SME, or see how governed execution fits your sector.
One governed engine from source to evidence
Create referenced drafts from approved knowledge, review and publish a version, then assign and run it through the same execution and audit model.
Explore the platformA funded route into the platform
FliT uses Holovast for reviewed onboarding and Learning Paths. It is a delivery programme over the shared platform, with browser and tablet as the baseline channels.
See the programmeEvidence-gated work where quality matters
Use governed guidance for assembly, inspection, maintenance, calibration, kitting, test, and other work where steps, evidence, and correction must stay connected.
See where we fitBring us one workflow where evidence matters
Too many AI projects stall between pilot and production. On Holovast, proving one workflow and deploying it are the same path.
Define the deployment scope
Select one high-impact workflow, target station, and baseline KPIs.
Run guided execution
Deploy guidance for live operators and monitor in-process adherence.
Review impact outcomes
Compare baseline and deployment results and agree scale-up priorities.