Sales and marketing lacked coding skills to query data. Now, an internal AI prompt store lets them pull instant answers in Salesforce.
A global payables automation platform processes $75 billion in transactions annually for hundreds of high-growth businesses.
Internal teams like sales and marketing needed timely insights but lacked the coding capabilities to query data effectively. Additionally, moving...
“The biggest benefit is that the insights are now always there for our people. If they want to analyze a certain opportunity or group of accounts, they can just log in, make a query, and it’s all there. They don’t have to think about how to build a prompt or manipulate data, they just get answers.”
Global payables automation platform for accounts payable and payment management.
Cloud-based data warehousing, processing, and analytics platform.
Tipalti's Self-service analytics is part of this use case:
Related implementations across industries and use cases
15 data domains, 20-minute queries, some tables too large to touch. One hackathon later, AI fields half of all queries—customers included.
Simple questions demanded 45 minutes of SQL. An AI assistant now answers 70% of internal analytics, freeing the team from routine queries.
Deep dives required formal requests to a small data team. Now, staff ask questions in Slack to spot upsell trends instantly.
15 data domains, 20-minute queries, some tables too large to touch. One hackathon later, AI fields half of all queries—customers included.
Deep dives required formal requests to a small data team. Now, staff ask questions in Slack to spot upsell trends instantly.
Scattered data and basic coding tools bottlenecked engineers. A 9-agent AI workflow shifts them from writing code to directing AI teams.
Sequential AI testing bottlenecked development. Engineers built a concurrent, code-first pipeline to evaluate agent responses in seconds.
With 99% of records missing metadata, teams sifted unlabeled databases. Now, AI generates column descriptions for data experts to verify.
Manual document summaries bottlenecked experienced staff. Now, AI drafts preliminary risk assessments, freeing teams for complex advisory.
Sales and marketing lacked coding skills to query data. Now, an internal AI prompt store lets them pull instant answers in Salesforce.
A global payables automation platform processes $75 billion in transactions annually for hundreds of high-growth businesses.
Internal teams like sales and marketing needed timely insights but lacked the coding capabilities to query data effectively. Additionally, moving...
“The biggest benefit is that the insights are now always there for our people. If they want to analyze a certain opportunity or group of accounts, they can just log in, make a query, and it’s all there. They don’t have to think about how to build a prompt or manipulate data, they just get answers.”
Global payables automation platform for accounts payable and payment management.
Cloud-based data warehousing, processing, and analytics platform.
Tipalti's Self-service analytics is part of this use case:
Related implementations across industries and use cases
15 data domains, 20-minute queries, some tables too large to touch. One hackathon later, AI fields half of all queries—customers included.
Simple questions demanded 45 minutes of SQL. An AI assistant now answers 70% of internal analytics, freeing the team from routine queries.
Deep dives required formal requests to a small data team. Now, staff ask questions in Slack to spot upsell trends instantly.
15 data domains, 20-minute queries, some tables too large to touch. One hackathon later, AI fields half of all queries—customers included.
Deep dives required formal requests to a small data team. Now, staff ask questions in Slack to spot upsell trends instantly.
Scattered data and basic coding tools bottlenecked engineers. A 9-agent AI workflow shifts them from writing code to directing AI teams.
Sequential AI testing bottlenecked development. Engineers built a concurrent, code-first pipeline to evaluate agent responses in seconds.
With 99% of records missing metadata, teams sifted unlabeled databases. Now, AI generates column descriptions for data experts to verify.
Manual document summaries bottlenecked experienced staff. Now, AI drafts preliminary risk assessments, freeing teams for complex advisory.