CONCENTRATE
Pricing
ModelsDocsRequest a Demo

Feature

Usage Analytics

Aggregate AI traffic into trends by model, provider, team, key, errors, tokens, and cost. Make route and model decisions from your own data, not a vendor slide.

Log inRead docs
Usage view

Volume, cost, latency, and error patterns grouped by model, provider, and owner.

Usage

Requests

Tokens

Input + output

Views

Team + model

Model

gpt-5.5

Request volume and spend over the selected range.

Provider

Anthropic

Usage grouped by provider route.

Team

Support

Owner-level view for reviews.

New capabilities

What your team gains with Concentrate

01

See which workloads drive volume

Group requests by team and key name to find the handful of workloads behind most of your token spend and request count.

02

Compare models head to head

See which model costs more for the same work, so a model choice is backed by your own numbers instead of a vendor benchmark.

03

Catch shifts before the invoice

Spot rising volume, slower responses, climbing cost, or a creeping error rate over time, while there's still room to change a route or fix a prompt.

Who Concentrate is designed for

What usage analytics add on top of request logs

Request logs are one row per call. Usage analytics roll those rows into comparisons and trends — which models drive the bill, which keys are growing — so engineering and finance can decide what to change without exporting spreadsheets by hand.

Engineering leads

Compare models on cost and token volume before changing a route or prompt.

Finance and operations

See which teams and keys drive cost over a billing period without opening separate provider consoles.

Platform teams

Spot a creeping error rate or traffic shift early, while you can still reroute or cap a key.

Built on request logs

Every chart traces back to request logs, so totals always reconcile to real calls.

Feature basics

Frequently asked questions

What should AI usage analytics include?
Useful AI usage analytics include request count, token count (input and output), cost, error rate, model, provider, key, team, and time window. Together these let you answer who used what, how much it cost, and whether it succeeded.
How do usage analytics help teams lower spend?
They show which workloads lean on expensive models, generate long outputs, fail and retry often, or could move to a cheaper route. Each of those is a concrete, measurable change rather than a guess.
How are usage analytics different from request logs?
Request logs are the row-by-row record of individual calls for debugging. Usage analytics aggregate those rows into trends and comparisons across models, providers, teams, and time, so they answer different questions for finance and engineering leads.
CONCENTRATE

One API for every major LLM provider — routing, spend, logs, and controls in one place.

New York

130 E 59th St, 17th floor

New York, NY 10022

Wilmington

1201 N. Market Street, Suite 200

Wilmington, DE 19801

LLM Gateway
  • LLM Gateway
  • Request Routing
  • Usage Monitoring
  • Spend Management
  • Data Security
  • Access Controls
Teams
  • AI Engineering
  • Engineering Leadership
  • Finance & Operations
  • Security & Compliance
Integrations
  • All Integrations
  • Migration Guides
Platform
  • Pricing
  • Model Fortress
  • Enterprise
  • Documentation
  • Status
Legal
  • Privacy Policy
  • Terms of Service
  • Data Processing Addendum
  • Acceptable Use Policy
Features
  • Universal API Keys
  • Spend Tracking
  • Token Allocation
  • Usage Analytics
  • Request Logs
  • Alerts
  • Data Redaction
  • Zero Data Retention
  • Audit Logs

LLM Gateway

  • LLM Gateway
  • Request Routing
  • Usage Monitoring
  • Spend Management
  • Data Security
  • Access Controls

Teams

  • AI Engineering
  • Engineering Leadership
  • Finance & Operations
  • Security & Compliance

Integrations

  • All Integrations
  • Migration Guides

Platform

  • Pricing
  • Model Fortress
  • Enterprise
  • Documentation
  • Status

Legal

  • Privacy Policy
  • Terms of Service
  • Data Processing Addendum
  • Acceptable Use Policy

Features

  • Universal API Keys
  • Spend Tracking
  • Token Allocation
  • Usage Analytics
  • Request Logs
  • Alerts
  • Data Redaction
  • Zero Data Retention
  • Audit Logs

Offices

New York

130 E 59th St, 17th floor

New York, NY 10022

Wilmington

1201 N. Market Street, Suite 200

Wilmington, DE 19801

© 2026 Concentrate AI. All rights reserved.

CONCENTRATE
Log In
Log In