LeanSignal vs New Relic

New Relic is an all-in-one platform on an aggressively agentic AI trajectory. This page credits that trajectory accurately, then draws the contrast on what the meter is attached to. Pricing and feature claims are as of mid-2026 and linked to their sources — verify before relying on them.

Where New Relic is genuinely strong

• Agentic ambition, shipped. New Relic AI went GA in June 2025 and has compounded fast: GitHub Copilot and ServiceNow integrations, an MCP server, a no-code Agentic Platform for custom observability agents, and an “Autopilot” direction — deeper agentic workflow reach than most of the market.
• All-in-one consolidation. One platform covering APM, infrastructure, logs, browser/mobile, and synthetics, with NL→NRQL and incident-aware Response Intelligence layered across it.
• Real admin controls. A Feature Control Manager (per-capability on/off), a compute-usage dashboard, and no charge for failed queries.

The structural difference

New Relic prices three meters stacked together: data ingest ($0.40–0.60/GB), user seats (up to $349/user/month), and — since GA — the AI, gated behind the Advanced Compute SKU and metered in CCUs at ~$0.60/CCU. CCU consumption tracks feature usage, not data volume or declared value, which makes it hard to forecast: rates are sales-gated rather than published, and analyses document month-over-month jumps from $900 to $8,000. Routine operation meters — a dashboard refreshing every minute is thousands of queries a day.

	New Relic	LeanSignal
Where filtering happens	Downstream of central ingest	At the edge, before storage — the demand set filters at the source
What cost is anchored to	Ingest volume + seats + metered compute (CCUs)	Declared demand — saved dashboards, active alerts, ingestion rules
Cost predictability	Usage-metered; rates sales-gated	Published math; hard caps; new cost only from new need
Standards	OTel supported alongside proprietary agents, NRQL	OpenTelemetry in, PromQL/LogQL out

The AI cost model

As of mid-2026, the assistant requires the Advanced Compute SKU and draws CCUs on top of ingest and seats — the AI is packaged as a third meter on a platform that already meters volume and people.

LeanBuddy is the counter-model on both axes. The unit math is published — 1 credit = 1 cent, cost-weighted tokens, default allowances stated on the page — and the caps are hard: when the daily allowance is spent, the assistant stops until midnight UTC. It never converts into an unbounded line item. And it searches a store that holds only demanded telemetry, so there is structurally less for any query — metered or not — to grind through.

The reframe: New Relic meters the assistant’s compute. LeanSignal caps it — and shrinks what it has to compute over.

Where New Relic is the right choice

• You are standardized on New Relic and want agentic AI wired into GitHub Copilot, ServiceNow, and incident workflows today — that integration depth has no LeanSignal equivalent.
• You want to build custom observability agents on a vendor’s no-code agentic platform.
• Seat- and usage-based pricing fits how your organization budgets, and your query patterns are stable enough to forecast CCU spend.

Next steps

• How LeanSignal compares — the structural framing shared by every page in this section.
• Demand-driven observability — the model in full.
• LeanBuddy budgets — the assistant’s published cost model.