
Machine-linked knowledge
Keep the approved procedure, task recording and reviewer sign-off against the task and equipment.

Connect your tools, capture knowledge from real work, and prove who can do the job
Thomas Bellamy · Co-founder and CRO, Edplay
Count how many systems you’d open to answer that.
Who works here, on which shift
Who completed which course
Who was signed off, and when
Deviations, NCRs, CAPAs, audit findings
What broke, and who fixed it
How the job is really done
Every person, skill, machine and site in one view. Approved knowledge linked to each task.
A team is at 61% against an 85% standard. The approved training exists.
→ Assign it to that group.
There isn’t enough approved material to teach it. It lives in someone’s head.
→ Capture the real work first.
“Most quality defects arise from procedure deviations, incomplete understanding of requirements and inconsistent execution.” · Senior operations leader, medical device manufacturing
Line clearance on a contact lens blister packaging line, captured hands-free and turned into an approved course.
Source: approved SOP and recorded repair on this equipment
Get the approved step mid-job, in your language.
The next person sees what was found and fixed last time.
What people ask shows where the gaps really are.
Approved SOPs, task videos and linked skills, in the worker's language.

Build training and onboarding from existing SOPs, task videos and the expert's explanation.
Use interactive formats and microlearning, aimed at the learning objective and audience.
AI prepares the draft. People review and publish the method the floor will follow.
One standard template for every SOP and course.

Keep the approved procedure, task recording and reviewer sign-off against the task and equipment.

Know which training addressed which gap, on which task, and how many retests it took.

Gap detection becomes useful when it leads to verified training, retesting and recorded competence.
AI content alone is not proof that someone can do the job.
Gap closure rate. Gaps closed against your baseline, on your own competence scale.
Time to competence. Days from a gap being found to qualified sign-off.
Retest pass rate. Share passing on the first retest, not just completion.
Reviewer edit rate. How much qualified reviewers change the AI draft.
Compare against your own baseline, not industry averages. Connect it to scrap, downtime or first-pass yield.
Built to connect with: SAP · Workday · ADP · Paylocity · ServiceNow · Oracle
Your environment or ours. On-premise, your cloud tenant, or isolated single-tenant.
Zero external model training. Your SOPs and recordings never train outside AI.
Encrypted end to end. AES-256 at rest, TLS 1.3 in transit.
Governed by your rules. Bystander face protection, role-based access to footage.
Turn the SOPs, videos and training you already have into approved material, in one standard template.
Moves: hours per item, time to independent work
Connect the systems you already run, see who knows what on which machine, and find the gaps.
Moves: skill gaps closed, unplanned stops
Add hands-free capture on the floor and roll out across lines and sites.
Moves: time to fix a fault, scrap and rework
Proposed scope, not a commitment. Leave with trusted knowledge, measured evidence and a rollout decision.
Ask “who can run line 3 tonight?” Count the systems it takes to answer.
Sort your open gaps: skill gap or knowledge gap?
Tie your next project to one number operations already tracks.


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