LLM observability, coming soon

You're spending real money on LLMs. You have no idea which features are burning most of it.

Gantry wraps your existing AI client in one line. See cost, tokens, and latency per feature — and which model switch saves the most, without touching your architecture.

Limited early-access spots remaining

No spam. No credit card. We email you once — when it's live.

See it live

Overview

§ Cost, tokens and latency across every model
⌘K
Last 30 days ▾

Total cost

$128,430

▼ 12.4%vs prior

Tokens processed

1.94B

▲ 8.1%vs prior

Requests

4.21M

▲ 5.4%vs prior

p95 latency

842ms

within SLA

Model Advisor

Live
Cheaper models that hold quality on your traffic
updated 4m ago
summarization−$18.6K
chat-support−$24.5K
classification−$10.7K
extraction−$10.6K
Feature tagclassification
Now servingGPT-4o
Volume88M tok / mo
Calls6.1M calls
Estimated monthly savings
$10,700
−73% · $128,400/yr · 88.1% eval vs 89%
Monthly cost · 3 candidates
GPT-4ocurrent
$14,60089.0%
Mistral Large 2rec
$3,90088.1%
GPT-4o mini
$2,10084.7%

Estimates replay your last 30 days of traffic against published vendor pricing and Gantry's eval suite. Routing affects new requests only.

Your real spend, traced per feature — the moment you wrap your client.

The problem is structural,
not a missing dashboard.

Global API traffic

Your LLM spend is split across dozens of features. You can't see which one is the problem.

🌐 Last spike from GPT-4o autocomplete
Live monitoringSample data

GPT-4o on a simple autocomplete costs 10× more than it needs to. You won't know until you compare real traffic.

14:32:01/api/summarizeSPIKE
gpt-4o$0.042·1.2s
14:32:04/api/autocompleteSLOW
gpt-4o$0.038·4.8s
14:32:09/api/classifyOK
claude-haiku$0.003·0.4s
$0.143 tracked · 6 calls · last 30srouting saved ~$0.08
Cost by model · last 6 months

Your latency looks fine at p50. At p95 it's breaking your UX. Nobody's measuring it per feature because there's no easy way.

Cost attribution

Per feature, per model, per call. Aggregate spend isn't enough. Know exactly which endpoint is bleeding money.

Latency tracing

p95 visibility out of the box. Tag and trace LLM calls at the granularity your team actually needs.

Integrate in one line of code

A drop-in wrap around your existing client. SDKs for every language you ship in, and any OpenAI-compatible endpoint — no migration, no new infrastructure.

1
2
3
4
5
6
7
8
9
10
11
12
import { Gantry } from '@gantry/sdk'
import OpenAI from 'openai'
 
const gantry = new Gantry({ apiKey: process.env.GANTRY_KEY })
// wrap once — same client, now traced
const client = gantry.wrap(new OpenAI())
 
const res = await client.chat.completions.create({
  model: 'gpt-4o',
  messages,
  gantry: { feature: 'summarization' },
})
traced automaticallytrace.ts · OpenAI

What you're getting
early access to.

Six capabilities shipping at launch. One SDK, one integration line.

01

Real-time cost tracing

Cost, tokens, and latency for every request, broken down by model, feature tag, and environment.

// live traceSAMPLE
→summarize$0.019824ms
→extraction$0.007432ms
→chat$0.0321,411ms
02

Model Advisor

Replays your real traffic against cheaper models with eval scores.

Coming at launch
monthly cost · 100M tokens/mo
GPT-4o
$1.5k
Mistral Large
$300
savings−$1.2k/mo
03

SDK-native, zero infra

One wrap around your existing client. No agents, no sidecars, no proxy to operate.

$npm install @gantry/sdk
04

Every provider, one view

OpenAI, Anthropic, Google, Mistral, and any OpenAI-compatible endpoint, normalized into a single ledger.

+any

+ any OpenAI-compatible endpoint

05

Spike & budget alerts

Set per-feature and per-model budgets. Get alerted the moment spend spikes — before it shows up on the invoice.

⚠/api/summarize·+312%$0.042/call
06

Per-feature attribution

Tag every call with a feature name. See exactly which feature, model, and environment is driving cost — no guessing from aggregate bills.

spend by feature
summarize
48%
chat
31%
extraction
21%

The math

The savings aren't a projection.
They're basic math.

$1.2k
saved / mo
Live pricing

On 100M tokens / month

Routing your summarization layer from GPT-4o to Mistral Large keeps output quality identical. Gantry does this per-feature, automatically.

GPT-4o$1.5k/mo
Mistral Large$300/mo
Difference$1.2k/mo · same task tier

$15 / 1M tokens (GPT-4o) · $3 / 1M tokens (Mistral)

These are public list prices from each provider's pricing page. Your actual savings depend on your traffic mix and quality requirements. That's exactly what Gantry shows you.

Questions.

We're in active development. Waitlist members get notified before anyone else, and early access spots are limited.

OpenAI, Anthropic, Google, Mistral, any provider with a Python or JavaScript client. If you're using a provider not on this list, tell us when you join.

No. Gantry wraps your client locally. Only metrics and metadata leave your infrastructure, your prompts and completions never touch our servers.

Free tier at launch. Pricing will scale with usage. Waitlist members hear pricing details first.

Early access · Limited to 500

Find out what you're actually spending —
before the next invoice does.

One line of code. Every token, every model, every feature — traced. Join the first 500 engineers to get access at launch.

Limited early-access spots remaining

No spam. No credit card. We email you once — when it's live.