Fuseline
A database connection gateway that gives each agent an identity, estimates and meters query blast radius, and enforces operator-approved budgets against a protected read path.
AI agents can generate valid, permission-allowed queries whose scans, retries or lock behavior still harm a production database or create unexpected infrastructure cost. The supplied research confirms the problem in industry incident discussion and finds adjacent query-optimization and open-source connection-pooling tools, but no reviewed product dedicated to agent query cost and blast-radius enforcement at the connection layer.
Fuseline gives each agent and task a distinct identity and routes the first release only to a redacted read replica. It parses the query, applies static policy, requests a bounded plan estimate where safe and compares predicted scan, rows, duration and concurrency with operator-approved budgets. It may allow, reject, queue or require approval. Runtime meters record actual behavior and can cancel under a separately tested rule.
Permission and resource safety remain independent: a query may be authorized yet too expensive, or inexpensive yet forbidden. An estimate is not actual cost; replica success is not primary safety; cancellation acknowledgment is not proof that work stopped; and a returned result is not correct analysis. The gateway must preserve these states and fail visibly when it cannot attribute or estimate a request.
The first release should support one database family, one read-only replica and two agent identities. It must not rewrite queries silently, route to the primary, infer monetary cost without an approved model or use captured SQL as training data. The accumulating trip history can improve tenant-specific thresholds, but portability and bypass detection matter more than connection-string lock-in.
Database platform or reliability leader responsible for protecting analytical data access from machine-generated query load
Recent industry discussion and documented cost incidents point to a current enforcement gap.
Agent-generated queries create a new volume and attribution pattern that makes connection-layer budget enforcement timely.
The record contains two cross-reference mentions, one inbound connection and four direct connections.
The supplied research documents a current operational failure mode, confirms adjacent optimization and pooling layers and finds no reviewed runtime product centered on agent query budgets.
Buyer size and budget are incomplete, transparent interception is reliability-critical, cost estimates vary by database and workload, and observability or database incumbents can add similar controls.
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