Traces that fuel Confluent Intelligence.
One agent produces a trace. A production fleet produces a continuous stream of decisions, tool calls, outcomes, and failures. Paper Compute captures it. Confluent makes it durable, queryable, and actionable.
The Problem
AI agents continuously make LLM calls, invoke tools, access data, and take action. As customers move from a pilot to a fleet, that activity becomes a large, fast-moving behavioral dataset. Most of it disappears after each run, leaving operations and compliance without a fleet-wide record. The fix shouldn't be adopting another dashboard.
Open Core
tapes is open source infrastructure for agent telemetry. Cassettes are the components you attach to it—the Confluent cassette is a metered sidecar that streams derived telemetry into your Confluent Cloud. Deploy it yourself, or let Paper operate it for you.
Zero-instrumentation capture at the network layer. Records every LLM call, tool invocation, and execution path, then derives sessions, spans, and stats from the raw record. No SDKs. No code changes. One command.
The streaming export. A sidecar next to tapes that produces derived events—sessions, spans, stats, anomalies—to topics in your Confluent Cloud. One cassette, one config, no bespoke connectors. Raw session content never leaves your boundary.
Managed Paper operates the capture gateway and cassettes for you—same open schemas, same topics in your cluster, zero ops on your side.
Where Confluent Fits
As agent counts and run volumes grow, Paper Compute turns activity from every agent into one consistent event stream. Confluent Cloud—topics, Flink, Tableflow, and existing dashboards—is where that aggregate becomes durable, analyzable, and valuable.
High-volume agent telemetry lands as structured events—sessions, spans, stats, and anomalies—on topics in your cluster. Instead of isolated traces, customers get a durable behavioral stream across every agent, governed by their retention, ACLs, and schema registry.
Anomaly detection purpose-built for agent failure modes—stuck loops, token spikes, behavioral drift—runs across the live fleet, not one trace at a time. The Flink SQL is readable, editable, and runs in the customer's Confluent environment. Not ours.
One export cassette, configured for Confluent. It sits next to tapes, reads the derived stream, and produces to your topics. The same cassette design targets other sinks with a config change—never a bespoke connector per destination.
Confluent's Real-Time Context Engine feeds live context into agents. tapes captures what agents do with that context, and the cassette streams it back. Context in, telemetry out—a closed observability loop built on Confluent primitives.
Fleet-wide projections: sessions, spans, stats. Judgment outputs: anomalies, outcomes. Continuous, structured, schema-registered, and queryable at scale.
Raw session content: prompts, responses, tool payloads. Recorded by tapes, kept wherever tapes runs. Projections can be rederived from it at any time.
Compliance reads the derived stream in Confluent. The raw record never has to leave.
Real-Time Anomaly Detection
Purpose-built for agent failure modes, evaluated continuously across the fleet: Flink SQL finds stuck loops, token spikes, and drift in the combined stream, then writes alerts to a topic in the customer's cluster.
Alerts don't stop at a dashboard. A consumer can write them back to a running agent as advice—the loop below is live code, not a diagram.
Proof: A Self-Healing Agent on Kafka
This architecture isn't a slide. An autonomous agent plays Pokémon Red headlessly inside a stereOS VM, and every battle, map change, and stuck loop streams through the exact pipeline on this page—while Paper records what the agent was thinking on the side.
The loop closes. Flink alerts become advice a live run polls between turns—parameter patches hot-applied mid-game, no operator involved. When tuning is exhausted, the evidence escalates to an engine that proposes a code change, runs the gates, and opens a PR. Telemetry out, healing in: the closed loop this page describes, running on a real workload.
pcc-labs/pokemon-kafkaIntegration Roadmap
List the Confluent cassette on the Hub so any Confluent customer installs it like a connector. The open topic schemas are the contract.
Turn the growing telemetry stream into queryable tables so operations, compliance, and security can analyze behavior across the fleet without engineering involvement.
Feed fleet-wide anomaly data back into the context engine so agents self-correct based on failures observed across every run—the advice-inbox pattern on Confluent primitives.
The Opportunity
One agent creates a trace. A fleet creates a continuously growingbehavioral dataset.
Every new agent workload creates another stream of decisions, tool calls, outcomes, and failures. Confluent customers can turn that volume into two answers their teams need:
The value compounds with scale. Every run enriches a durable dataset for real-time detection, historical analysis, benchmarking, capacity planning, and audit. It lands where customer teams already work—no new dashboard to roll out and no new vendor UI to learn.
Together, Confluent and Paper Compute give enterprises full-stack observability for agent fleets. Regulated industries—financial services, healthcare, defense—that already require audit trails for data pipelines will require the same for the agents operating on that data. Paper Compute creates the behavioral stream; Confluent makes it operationally useful; the raw record never leaves the customer's boundary.
Bring agent telemetry into the Confluent conversation.
When a customer is moving from one agent to a production fleet, every run becomes valuable streaming data. Paper Compute captures it and Confluent turns the volume into real-time insight. Bring us into the deal for a demo, architecture review, or joint customer call.
Confluent was acquired by IBM in 2025. For enterprise buyers, this means Confluent Cloud is now backed by IBM’s global support, compliance certifications, and procurement infrastructure. Paper Compute’s integration targets Confluent Cloud APIs and is unaffected by the change in ownership.