Industrial organizations generate thousands of task photos, videos, observations, and field reports — most of it unstructured and impossible to compare. HandSafety.ai turns that data into a structured, searchable exposure database across every site, plant, and operation.
Most organizations discover hand exposure after an incident report, not before — and even then, the finding lives in a single document, not a record they can search, compare across sites, or learn from. Risk lives in task design, equipment layout, and the last 300 millimeters between a worker's hand and a hazard, and almost none of it is captured anywhere comparable.
HandSafety.ai exists because exposure data is everywhere — in toolbox talks, near-miss notes, field reports, video walkthroughs — and nowhere structured. We turn it into a database your organization can query, compare, and learn from.
Exposure risk is a structured-data problem hiding inside field photos, task notes, videos, and incident records.
HandSafety.ai is built on the field doctrine, exposure taxonomy, and industrial task-mapping work developed by the team behind Hand Safety First® and Project Sales Corp — years of hand-exposure-specific research that most EHS software has no equivalent of.
Country-level exposure observatory and comparison reporting on hand-injury patterns across industrial sectors.
A structured reference covering hand-exposure failure modes, control measures, and field terminology across industries.
A field-tested method for locating exposure points within a task, independent of industry or equipment type.
Direct exposure to how hand-intensive tasks are actually performed across manufacturing, mining, oil & gas, and heavy industry.
HSF / PSC is the source of the doctrine, field knowledge, and exposure framework. HandSafety.ai is the software layer built on top of it — the database, AI structuring, and analytics that turn that doctrine into something searchable and comparable.
Every structured record runs through the same four-part method — so a finding from one plant is produced the same way as a finding from another, and you can ask exactly how the platform got to it.
The 300mm boundary used throughout HandSafety.ai's distance-based findings is built on HSF's Last 300mm Rule™ — the established doctrine that the last 300 millimeters between a hand and a hazard is where most exposure decisions actually get made.
Identifies every point in a task where a hand crosses into a hazard zone, before classifying what kind of hazard it is.
The eight-category schema — pinch, crush, line-of-fire, suspended load, impact, stored energy, hazardous interface, entrapment — applied consistently across every structured task.
Maps each exposure finding to a category of fix — engineering, distance, task redesign, procedure, tooling, handling method, or residual PPE — without prescribing a specific product.
The structuring method that turns an unstructured task description, photo, or video into discrete steps with exposure tags attached to each one.
The taxonomy HandSafety.ai runs on wasn't written in the abstract. It comes from direct field observation of hand-intensive tasks across the operations where hand exposure actually happens.
No new hardware, no workflow disruption. Your team uploads what already exists — the pipeline does the rest.
Photos, video, descriptions, observations, or existing procedures — in whatever format your sites already produce them.
The platform parses each input into discrete task steps, identifies hand-involvement points, and tags exposure categories.
Missing context, ambiguous steps, or insufficient detail are flagged explicitly — the system tells you what it doesn't know.
A qualified reviewer validates every finding, then it becomes a permanent, comparable record — searchable alongside every other task you've structured.
Breaks unstructured descriptions and footage into discrete, analyzable task steps.
Maps each step against eight hand-exposure categories: pinch, crush, line-of-fire, suspended load, impact, stored energy, hazardous interface, and entrapment.
Identifies missing detail, ambiguous distance or timing data, and flags it for clarification instead of guessing.
Produces a structured, evidence-linked draft — never a final determination — ready for expert review.
No two plants describe the same task the same way. The platform reads all of these regardless of how they're documented, and turns each one into a comparable database entry.
PINCH · CRUSH
LINE-OF-FIRE · PINCH
SUSPENDED LOAD
IMPACT · PINCH
IMPACT · LINE-OF-FIRE
HAZARDOUS INTERFACE
CRUSH · SUSPENDED LOAD
STORED ENERGY
A database is only as useful as the data that feeds it. No finding enters the exposure database without a qualified human in the loop — that's what makes every comparison and every benchmark trustworthy.
Generates structured first-pass exposure data, confidence scores, and explicit flags on every uncertain finding. Nothing here is presented as final.
A qualified reviewer inspects each draft against the source evidence, edits findings, and signs off. Every record carries a named reviewer and timestamp.
Validated findings join the exposure database as permanent, structured records — searchable, benchmarkable, and traceable back to source input and reviewer at any point.
Trends, heat maps, and recurring patterns — query your exposure history the way you'd query any other enterprise dataset.
High-cycle line work, automated cell interfaces, changeover tasks.
Heavy mobile equipment, suspended loads, remote-site review.
Drilling floor handling, pressure systems, rigging interfaces.
Energized equipment access, stored-energy isolation tasks.
Container handling, crane interfaces, multi-crew load transfer.
Variable task sites, rigging, formwork, and tool interface risk.
Steel, aluminium, and process plants with complex hazard layering.
Field crews, switching operations, line maintenance.
These categories are the schema behind the database — the common language that makes a finding from one site comparable to a finding from another. Each one is a recognizable pattern that shows up across industries and equipment types, and each one is detectable before the task is ever performed.
Two surfaces closing on a hand between moving and fixed components.
Sufficient force or mass to cause crush injury on contact.
A hand positioned in the path a load or component could travel if released.
Direct hand contact with a load under tension or in motion overhead.
Sudden, unguided contact from a moving object or surface.
Hydraulic, pneumatic, spring, or electrical energy not yet isolated.
The boundary where a hand must cross into a hazard zone to complete a task.
Every validated assessment points to a control family — a category of fix, not a specific product. What to actually implement is a decision for your engineering and safety teams, informed by the assessment.
Changes to equipment, guarding, or layout that remove the hand from the hazard entirely.
Methods that increase the distance between a hand and an active hazard during the task.
Restructuring the sequence or assignment of a task so the exposure step is no longer required.
Updated written procedures that change how, when, or by whom a task is performed.
Introducing a tool-mediated step between the hand and the hazard, without prescribing a specific tool.
Changes to grip, positioning, or technique that reduce exposure during manual handling.
Personal protective equipment is recommended only as a last layer, after other controls have been assessed.
Control families are presented as categories for your team to evaluate. The platform does not recommend, sell, or endorse any specific product, tool, or brand.
Every layer is designed to feed the same underlying database — auditable, versioned, and queryable across every site you add.
Industrial task data is sensitive by nature. The platform is built around strict tenant isolation and minimal retention by default.
Every organization's task data, footage, and assessments live in an isolated environment. Nothing is pooled or cross-referenced across customers.
Uploaded photos, video, and task descriptions are never used to train shared models without explicit, separate consent.
Granular permissions for plant teams, safety leadership, and reviewers — visibility scoped to what each role needs.
Every assessment retains its source evidence, AI draft, reviewer identity, and edit history — permanently.
Standard enterprise-grade encryption across all storage and transmission layers.
Organizations control how long raw media is retained after an assessment is finalized.
We're building a common language for industrial exposure — one structured enough that a pinch point in a steel mill and a pinch point on a drill floor are comparable, searchable, and benchmarkable against each other. As the database grows across sites, departments, and contractors, exposure stops being a once-a-year audit finding and becomes a number operations leaders track continuously, the same way they track cost and throughput.
No. The platform drafts and structures findings; a qualified human reviewer validates every assessment before it's finalized. It's built to make your safety team faster and more consistent, not to replace their judgment.
No. The platform works from inputs you already generate — task descriptions, photos, video, and field reports — with no new hardware deployment required.
It says so. Every draft assessment carries explicit confidence indicators and flags missing information rather than filling gaps with assumptions.
No, not without separate, explicit consent. Customer data is isolated by default and is not pooled across organizations.
HandSafety.ai is designed to sit alongside existing SMS and EHS platforms, producing structured exposure records that can be exported or integrated rather than replacing what you already run.
Cross-site benchmarking only ever happens within your own organization's data — across your plants, departments, and contractors. We don't pool or compare your exposure data against other customers without separate, explicit agreement.
Bring five critical tasks. We'll structure them, validate them, and show you the first entries in a database built to grow across every site you add — confidential, and yours to keep.
Tell us about your operation and we'll set up a private workspace for your first five tasks — the seed of your own structured exposure database, AI-structured and human-reviewed from the first upload.
No PPE. No products. No catalog. Just exposure intelligence.