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Heat is linked to an estimated four hundred
and eighty-nine thousand deaths a year,

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and two point four billion of the world's
workers are likely to be exposed to excessive
heat on the job.

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The people most at risk are the least likely
to get a warning they can act on.

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A weather app tells you it's forty-one
degrees.

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HeatShield tells you what to do about it: for
your body, your job,

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and in your own language.

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Here's an outdoor worker in Dubai.

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HeatShield takes the live forecast and
computes the heat index used by the US
National Weather Service:

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the risk right now, when it peaks, and this
person's risky hours.

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Hour by hour, the chart shows where the heat
is heading.

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Then Amazon Bedrock writes a short action plan
in Arabic: three concrete steps and the
warning signs,

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grounded in CDC and NIOSH guidance.

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Two reviewer agents check its language and its
safety before anyone sees it.

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For anyone who finds reading hard, Amazon
Polly reads it aloud.

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Switch the language, and a coworker gets their
own plan in Hindi.

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HeatShield writes plans in thirteen languages.

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Nobody has to remember to check.

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Every hour, EventBridge Scheduler re-scores
everyone, and Amazon SNS emails anyone whose
risk reaches their personal alert level:

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at most once per level each day, and never at
night.

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This is a real inbox.

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The six a.

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m.

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alert was sent by the schedule on its own,
before the heat of the day.

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HeatShield is built for communities.

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A foreman, a teacher or a clinic worker shares
one invite link and watches the whole group on
a private dashboard,

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worst risk first.

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Kai, the coordinator agent, plans who to check
on first and by when,

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across time zones, and for outdoor workers,
the safest eight-hour shift,

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computed from the forecast.

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Behind it are eight AI agents, and you can
watch them work in Agent HQ,

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drawn live from their real runs.

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Each one pairs a real algorithm with a model.

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Sol detects heatwaves against each city's own
climate, and reads fifty-one ensemble
forecasts,

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so a warning says how likely it is.

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Quinn audits the forecast every day: every
missed Danger day and every false alarm is
counted by code,

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not by the model.

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And anyone can ask the team a question, in any
of the thirteen languages.

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Kai assigns it to the right agents, who answer
with their real tools.

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Here, Sol finds Karachi, and Kai searches the
forecast for the crew's safest shift.

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Now a harder one: a coworker showing signs of
heat stroke.

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Nothing a model writes is trusted on its own.

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Code makes the final call: every number in an
answer must come from a tool,

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a health answer that skips the vetted facts is
sent back, and phone numbers,

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medicines and doses are blocked.

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So the answer starts with calling the local
emergency number,

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followed by the vetted first-aid steps.

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Even the model was chosen by measurement: five
Bedrock models answered the same questions,

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and the most accurate one now coordinates the
team.

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It's fully serverless on AWS, in one SAM
template: CloudFront and S3,

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API Gateway and nine Lambda functions,
DynamoDB, EventBridge Scheduler,

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SNS, Polly, Cognito for the operator console,
and Amazon Bedrock behind every agent.

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Failed runs are retried and kept, nine
CloudWatch alarms email the operator,

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and a measured daily AI budget caps the
spending without ever stopping the alerts.

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Even this voice is Amazon Polly.

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It's live right now.

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HeatShield: from forecast to action, in your
language.
