High-performance
AI classification

Beats GPT-5.4 accuracy · up to 100x cheaper · real-time latency

Self-calibrating accuracyNo prompt engineering
Try examples
billing×technical_support×sales×spam×
Model
Label
Conf
Latency
Cost/1M
classer
technical_support
1.00
0.09s
$8
GPT-5.4-mini
technical_support
0.95
5.91s
$515
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Built for our own apps. Now open to everyone.

The Problem

You're overpaying for most AI tasks

You need to sort a support ticket. Detect spam. Route a phone call. Tag a product image. So you:

1

Iterate Prompts

Rewrite "be accurate" 47 ways until the model stops making things up.

2

Debug Schema Violations

Catch the 15% of responses that ignore your output format.

3

Face the Bill

Watch costs explode when you scale past demo.

It works. But it's slow, expensive, and embarrassingly over-engineered for a task that should take milliseconds.

The Solution

A dedicated engine for the 90% of AI tasks

We stripped away the "chat" and let the intelligence focus on: turning messy data into accurate labels.

1

No more prompt engineering.

Provide your labels and let the engine auto-calibrate. No "Act as" fluff, no manual tweaking.

2

Zero schema violations.

Pure classification means zero hallucinations. Get the right format, every single time.

3

10x lower overhead.

Scale without the "LLM tax." Built for high-volume apps where speed and margins matter.

It's precise. It's predictable. It's the specialized infrastructure for the 90% of AI tasks that don't need a chat interface.

Comparison

How we compare to General-Purpose LLMs

Primary Goal

Classer: High-speed classification

LLM: Human-like conversation

Setup

Classer: 60-second "Zero-shot"

LLM: Weeks of prompt engineering

Developer Cost

Classer: Low. Non-technical "Correct" loop.

LLM: High. Senior devs babysitting prompts.

Latency

Classer: Deterministic (< 200ms)

LLM: Variable (Seconds)

Reliability

Classer: 100% Valid Outputs

LLM: 15% Schema violations

Cost

Classer: $ (Input tokens)

LLM: $$$ (Input + Reasoning tokens)

Benchmarks

Tested on 33 public datasets

Classer beats GPT-5.4-mini on the top classification benchmarks — with zero training data.

Average

75.8%

Classer

vs

Average

67.7%

GPT-5.4-mini

DatasetClasserGPT-5.4-mini
LexGLUE ECtHR63.0%15.6%
Financial PhraseBank69.8%24.1%
LexGLUE Unfair-ToS58.5%24.9%
LexGLUE SCOTUS70.0%44.5%
App Reviews65.0%40.5%
Sarcasm Detection76.0%58.0%
RumourEval84.5%71.0%
TREC Question94.5%81.5%
SMS Spam97.0%90.5%

The Journey

Start in 60 seconds. Improve without ML engineers.

1

Zero-shot

Just pass your labels. It works out of the box.

2

Monitor

See every prediction in your console. Inspect confidence scores. Spot edge cases.

3

Correct

Add class descriptions. Label a few examples, or let a high-reasoning LLM do it automatically.

4

Auto-improve

Enable auto-calibration. The system distills your data into a custom model that lives in your account.

You stay focused on your product. The model gets smarter in the background.

PRICING

Predictable, low-cost AI pricing

Pay for input tokens only. Choose the priority tier and save up to 8x vs public LLMs.

PriorityPrice / 1MLatency
Fast$0.60<200msP95
Standard$0.20<1sP95
Fast Batch$0.08<15minP95
Free tier: 10M tokens/mo free - no credit card required
Enterprise: Need volume pricing or dedicated infra? Contact us

Fast Batch Processing

Millions of results in 15 minutes

No concurrency scriptsNo retry loopsNo rate limit workaroundsNo 24-hour waits

Just upload a file — up to 50 million rows per job — and get labeled results back at whatever scale your pipeline needs.

Lowest cost

If you don't need instant answers, Batch is the cheapest way to run Classer

FAQ

Frequently Asked Questions

Stop burning money

Get your API key in 30 seconds. First 10M tokens free.

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