Theblueconomy
Blueconomy AI provides Beam, an analysis layer for customer-facing AI agents in production that connects agent telemetry with downstream customer outcomes like escalations, repeat contacts, and CSAT scores. The platform clusters thousands of executions into recurring behavioral patterns, ranks them by measured customer impact, and identifies likely causes with supporting evidence so engineering teams can prioritize fixes. Beam supports OpenTelemetry and API-based ingestion, integrating with existing agent telemetry without intervening in conversations.
- Data & Analytics
- Artificial Intelligence
- Developer Tools
- Software Only
Funding
Funding not disclosed
Founders
Founder details are not available yet.
Product
Problem
Existing tracing and observability tools only reveal issues within a single execution, missing recurring failure patterns that span thousands of conversations with customers. AI agents can fail in ways that return successful status codes at every step while still causing escalations, repeat contacts, and low customer satisfaction, leaving engineering teams blind to the behaviors that actually harm the business.
Solution
Beam is an analysis layer for customer-facing AI in production that reads the telemetry agents already emit—traces, tool calls, retrieval steps, and conversations—and connects it with what happened to the customer afterwards, including escalations, repeat contacts, resolution, and CSAT scores. The platform groups thousands of executions into recurring behavioral patterns, attaches the customer outcome to each pattern, and ranks them by measured customer impact. For each issue, Beam identifies likely causes with supporting evidence such as affected conversations, shared trace patterns, tool sequences, and deployment windows, so engineers can quickly confirm or reject the diagnosis. Beam does not intervene in conversations or fix problems itself; it surfaces and prioritizes production issues so engineering teams can ship the fixes.
Target Audience
Engineering teams responsible for production AI agents at companies deploying customer-facing AI systems, particularly those who need to understand how AI behavior impacts customer experience and business outcomes.
Features
- Clusters recurring AI failure patterns across production traffic rather than analyzing individual traces
- Correlates agent telemetry with customer outcomes including escalations, repeat contacts, resolution status, and CSAT scores
- Ranks issues by measured customer impact so teams can prioritize fixes that matter most
- Provides likely cause identification with supporting evidence from conversations, trace patterns, tool sequences, and deployment windows
- Supports OpenTelemetry and API-based ingestion for integration with existing agent telemetry
- Delivers results as a ranked list of production issues with affected conversations and shared behaviors