AWS’s new AI agentic platform aims to automate business workflows

The modern enterprise has more data than it can handle, and AI agents are increasingly stepping in to help.

AWS aims to tackle that data overload with its new Amazon Quick Suite, an agentic AI system released Thursday that can conduct deep-dive research, answer questions, analyze and visualize data, and automate workflows.

The company claims the AI-driven system has slashed the time required for research analysis from months to 20 minutes, and helped solve complex customer queries in 15 minutes rather than hours.

“In a sea of AI-powered applications, it’s becoming increasingly difficult for customers to determine which tools to choose,” noted Justin Tung, a senior principal analyst with Gartner. “This is going to be an attractive offering for those who are already familiar with or are heavy users of other products in Amazon’s tech portfolio.”

Connecting disparate systems

“The typical enterprise, regardless of size, often struggles with putting together data from different sources into a single location for analysis and data exploration,” Tung notes.

Quick Suite syncs information across internal repositories such as wikis and intranets, and features a Quick Index system with more than 50 built-in connectors for apps, including Adobe Analytics, Amazon S3, Databricks, Google Drive, Outlook, Salesforce, ServiceNow, Slack, and Snowflake.

The platform can also access more than 1,000 server integrations, including Atlassian, Asana, Box, Canva, PagerDuty, Zapier, and others, via model context protocol (MCP), the open-source standard for connecting tools with data sources.

By unifying all this information, the company says that Amazon Quick Suite can recap emails and answer in-depth questions, send messages, automate content generation, create visualizations, update Jira tickets, build customer strategies, and write case studies.

For instance, a marketing manager doing competitive benchmarking analysis in preparation for a product launch can create a custom agent or agents, and instruct them to “summarize the generative AI software marketing landscape.”

The agent can then put together an executive summary including metrics and detailed data analysis, and make suggestions around campaign messaging adjustments or increased investments. Agents can also consolidate campaign performance data and other information. This gives teams a broad view of the market through surveys, industry reports, specialized datasets, competitor web pages, user forums, and social media sentiment.

Going forward, agents can then send out automated email and Slack notifications as soon as new campaign insights become available, allowing teams to adjust campaigns on the fly.

The new suite “can provide quick data crunching and analysis without the need for highly technical personnel, which will be a major boon to the business user,” noted Tung.

Quick Suite’s integration with popular enterprise data sources can “to some extent” help alleviate businesses’ concerns about being locked into a single platform or ecosystem, allowing for data usage across platforms and vendors, he said.

How AWS and its customers are using Quick Suite

AWS says it has been testing Quick Suite extensively internally and with hundreds of beta customers across healthcare, travel, manufacturing, and other industries.

For instance, an AWS program manager built a custom flow to report on new, in-progress, and closed Asana tickets for a week, compare them to other weeks, and generate summary emails. This saved “multiple hours of manual work” every week, the company claims.

Quick Suite can also handle complex multi-turn systems requiring hundreds of steps across different systems. For example, Amazon’s finance team was able to reconcile thousands of invoices every month, using the platform to pull information from multiple external transportation management systems, cross reference with internal data to help forecast cashflow, identify issues blocking payments, and conduct root cause analysis.

The team built this automation without the need for a developer team, reducing what could have been weeks of work to days, according to AWS.

Further, the company’s last mile delivery team used Quick Suite to assess the impact of new legislation in a particular country. In 30 minutes, agents were able to deliver an in-depth analysis, which typically would have taken multiple team members two weeks to complete.

Marketing automation company Propulse Lab had similar results when it created agents that can handle incoming customer service tickets. With human-in-the-loop validation and one-click approvals, Quick Suite agents have been processing 1,600-plus monthly tickets, reducing average time spent by 80%. CEO Alienor Carre-David said the company aims to serve 15,000-plus tickets monthly, and predicts it will save more than 24,000 hours annually.

Meanwhile, engineering, supply chain, and manufacturing company Jabil has optimized accounts collection and request for quote (RFQ) submissions with the use of agents, saving roughly $400,000 annually, according to Jabil CIO May Yap.

“Conversational BI features enable our teams to access faster, deeper insights … while Quick Suite provides timely expert and regulatory updates across key industries,” said Yap.

An overwhelming number of AI options

That said, experts point out that we’re in the early days with agents, and they’re still proving their worth.

While Gartner predicts that AI spending will total nearly $1.5 trillion this year, the current supply of agentic AI models, platforms, and products “far exceeds” demand.

A recent survey by the IT consulting firm found that only 5% of IT leaders are considering, piloting, or deploying fully autonomous AI agents. This may soon lead to consolidation and market correction, the firm says.

Quick Suite’s success is still in question, Tung notes: “We’ll have to see how it stacks up against similar competitor offerings in the market over the longer term.”