Local modeling limited output to 5 projects. Now, 2,000 users build their own models on a shared platform, scaling production 12x.
A logistics real estate firm operating in a fast-paced industry, where data science initially relied on a traditional warehouse setup and siloed development.
Data scientists built models on local machines using static extracts, requiring manual handoffs that often delayed deployment until insights became...
“Analysts can come in, they get seamless integrations with all of our data source systems. They can do EDA, build models, build web apps or dashboards. It's very powerful and it's enabled a lot of our users.”
Real estate investment trust specializing in logistics and industrial warehouses.
AI and machine learning platform for enterprise data science and analytics.
Prologis's Self-service analytics is part of this use case:
Related implementations across industries and use cases
Seven brands, SQL Server 2002 to BigQuery—Monday's request landed Wednesday. Now a Slack question gets answered in seconds.
Telemetry from 6M machines was trapped in internal silos. Unifying it into a shared platform lets customers deploy predictive AI.
Deep dives required formal requests to a small data team. Now, staff ask questions in Slack to spot upsell trends instantly.
Fragmented tools slowed operations. A unified platform now connects experts and business users, cutting analysis time by 60%.
Manual exports caused five-hour lags. AI cut fuel stockouts by 20% and audit prep from two weeks to one hour.
Human sales teams clock out; buyers don't. Voice agents, accent-matched by region, now qualify and book site visits around the clock.
Surging delinquency burdened staff. Now, an AI assistant handles routine collections, freeing teams for high-touch, in-person engagement.
Scaling AI access across a 100,000-employee workforce risked system overloads. An auto-scaling platform launched with zero downtime.
Energy market research that took weeks now closes same-day. Staff freed from chasing information to make the calls that matter.
Local modeling limited output to 5 projects. Now, 2,000 users build their own models on a shared platform, scaling production 12x.
A logistics real estate firm operating in a fast-paced industry, where data science initially relied on a traditional warehouse setup and siloed development.
Data scientists built models on local machines using static extracts, requiring manual handoffs that often delayed deployment until insights became...
“Analysts can come in, they get seamless integrations with all of our data source systems. They can do EDA, build models, build web apps or dashboards. It's very powerful and it's enabled a lot of our users.”
Real estate investment trust specializing in logistics and industrial warehouses.
AI and machine learning platform for enterprise data science and analytics.
Prologis's Self-service analytics is part of this use case:
Related implementations across industries and use cases
Seven brands, SQL Server 2002 to BigQuery—Monday's request landed Wednesday. Now a Slack question gets answered in seconds.
Telemetry from 6M machines was trapped in internal silos. Unifying it into a shared platform lets customers deploy predictive AI.
Deep dives required formal requests to a small data team. Now, staff ask questions in Slack to spot upsell trends instantly.
Fragmented tools slowed operations. A unified platform now connects experts and business users, cutting analysis time by 60%.
Manual exports caused five-hour lags. AI cut fuel stockouts by 20% and audit prep from two weeks to one hour.
Human sales teams clock out; buyers don't. Voice agents, accent-matched by region, now qualify and book site visits around the clock.
Surging delinquency burdened staff. Now, an AI assistant handles routine collections, freeing teams for high-touch, in-person engagement.
Scaling AI access across a 100,000-employee workforce risked system overloads. An auto-scaling platform launched with zero downtime.
Energy market research that took weeks now closes same-day. Staff freed from chasing information to make the calls that matter.