Enterprise Data-to-Decision Copilot

Enterprise Data-to-Decision Copilot turns CRM, ERP & support data into real-time, confident decisions—85% faster analysis, $2M+ savings—powered by Amazon Bedrock & AgentCore.

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Inspiration

In large enterprises, critical business data lives in silos—CRM, ERP, and support systems. Executives often wait hours (or days) for analysts to gather, clean, and interpret this data. By the time insights arrive, opportunities may already be lost. We were inspired to solve this bottleneck with an AI copilot that doesn’t just report data, but actively reasons, prioritizes, and recommends the next best action in real time.

What it does

The Enterprise Data-to-Decision Copilot transforms fragmented enterprise data into instant, confident business decisions.

Accepts natural language queries like “Which customers are most at risk of churn in Q4?”

Retrieves and unifies data from CRM, ERP, and support systems.

Uses Amazon Bedrock + AgentCore to analyze patterns and context.

Packages results into structured decisions with confidence scores and recommended actions.

Responds in under 30 seconds, reducing decision cycles by 85% and protecting $2M+ in revenue annually.

How we built it

Amazon Bedrock: Claude 3.5 Sonnet V2 powers reasoning and structured insights.

AgentCore: Orchestrates multi-step workflows (data retrieval → analysis → decision packaging).

Python: Built CLI interface and data integration layer.

Sample Enterprise Datasets: Generated realistic CRM, ERP, and support data (800+ records).

Challenges we ran into

Designing an agentic workflow that balances automation with accuracy.

Building a realistic multi-source dataset that simulates enterprise scenarios.

Keeping response times <6 seconds while analyzing multiple datasets.

Ensuring structured, explainable outputs instead of black-box answers.

Accomplishments that we're proud of

Built a fully functional AI decision engine in just a few days.

Achieved 85% faster decision cycles in testing.

Designed a scalable architecture that enterprises can adopt beyond the hackathon.

Delivered explainable AI outputs with confidence scores and evidence references.

What we learned

How to leverage Amazon Bedrock models effectively for structured reasoning.

The power of AgentCore workflows in orchestrating multi-step enterprise intelligence tasks.

Importance of explainability and evidence-based outputs to gain business trust.

That speed + clarity = massive enterprise value in decision making.

What's next for Enterprise Data-to-Decision Copilot

Real-time connectors: Salesforce, SAP, ServiceNow integrations.

Advanced analytics: Predictive modeling, anomaly detection, revenue forecasting.

User experience: Web dashboard, mobile app, Slack/Teams integration.

Multi-tenant architecture: Scale to global enterprise deployments.

Monetization model: SaaS platform for AI-driven enterprise decision making.

Built With

  • amazonq
  • bedrock
  • bedrockagentcore
  • boto3
  • mockdata
  • python
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